Experiments with lstm
In [16]:
from utils.paths import TMP_DIR
from utils.paths import ML_FLOW_DIR
from autoregression.utils_ar import prepare_direct_lstm_data,prepare_recursive_lstm_data, run_direct_lstm_experiment, run_recursive_lstm_experiment
from evaluation import evalresu as er
import mlflow
mlflow.set_tracking_uri(ML_FLOW_DIR)
In [2]:
import joblib
n_past_values=100
n_future_values=20
input_shape=(n_past_values,1)
Data preparation
In [3]:
data = joblib.load(TMP_DIR / 'output1_smoothed_RTS.pkl')
In [4]:
X_train_dir, y_train_dir,X_val_dir,y_val_dir,X_test_dir,y_test_dir = prepare_direct_lstm_data(data,n_past_values,n_future_values)
X_train_rec, y_train_rec,X_val_rec,y_val_rec,X_test_rec,y_test_rec = prepare_recursive_lstm_data(data,n_past_values)
Direct Multioutput Model
In [6]:
from autoregression.models.DirMultiLSTM import build_direct_lstm_model_simple,build_advanced_direct_lstm, build_direct_model_avg
Direct Simple 128 units
In [7]:
run_direct_lstm_experiment(
build_direct_lstm_model_simple,
'simple',
'direct_simple',
X_train_dir,
y_train_dir,
X_val_dir,
y_val_dir,
X_test_dir,
y_test_dir,
20,epochs=100,lstm_units=128)
Model: "Direct_LSTM_Model_simple"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_layer (LSTM) │ (None, 128) │ 66,560 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ output_layer (Dense) │ (None, 20) │ 2,580 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 69,140 (270.08 KB)
Trainable params: 69,140 (270.08 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 36ms/step - loss: 0.0243 - mae: 0.0787 - mse: 0.0243 Epoch 1: val_loss improved from inf to 0.00111, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 23s 41ms/step - loss: 0.0242 - mae: 0.0785 - mse: 0.0242 - val_loss: 0.0011 - val_mae: 0.0264 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 2/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 Epoch 2: val_loss improved from 0.00111 to 0.00108, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 0.0012 - mae: 0.0267 - mse: 0.0012 - val_loss: 0.0011 - val_mae: 0.0260 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 3/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 0.0011 - mae: 0.0254 - mse: 0.0011 Epoch 3: val_loss improved from 0.00108 to 0.00104, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 19s 37ms/step - loss: 0.0011 - mae: 0.0254 - mse: 0.0011 - val_loss: 0.0010 - val_mae: 0.0254 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 4/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 0.0010 - mae: 0.0251 - mse: 0.0010 Epoch 4: val_loss improved from 0.00104 to 0.00100, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 0.0010 - mae: 0.0251 - mse: 0.0010 - val_loss: 9.9734e-04 - val_mae: 0.0249 - val_mse: 9.9734e-04 - learning_rate: 0.0010 Epoch 5/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 0.0010 - mae: 0.0246 - mse: 0.0010 Epoch 5: val_loss improved from 0.00100 to 0.00094, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 21s 40ms/step - loss: 0.0010 - mae: 0.0246 - mse: 0.0010 - val_loss: 9.4094e-04 - val_mae: 0.0240 - val_mse: 9.4094e-04 - learning_rate: 0.0010 Epoch 6/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step - loss: 9.9055e-04 - mae: 0.0245 - mse: 9.9055e-04 Epoch 6: val_loss did not improve from 0.00094 517/517 ━━━━━━━━━━━━━━━━━━━━ 21s 41ms/step - loss: 9.9043e-04 - mae: 0.0245 - mse: 9.9043e-04 - val_loss: 0.0013 - val_mae: 0.0279 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 7/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step - loss: 8.9176e-04 - mae: 0.0230 - mse: 8.9176e-04 Epoch 7: val_loss did not improve from 0.00094 517/517 ━━━━━━━━━━━━━━━━━━━━ 21s 41ms/step - loss: 8.9176e-04 - mae: 0.0230 - mse: 8.9176e-04 - val_loss: 9.8547e-04 - val_mae: 0.0244 - val_mse: 9.8547e-04 - learning_rate: 0.0010 Epoch 8/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 40ms/step - loss: 8.8060e-04 - mae: 0.0229 - mse: 8.8060e-04 Epoch 8: val_loss did not improve from 0.00094 517/517 ━━━━━━━━━━━━━━━━━━━━ 23s 45ms/step - loss: 8.8063e-04 - mae: 0.0229 - mse: 8.8063e-04 - val_loss: 0.0013 - val_mae: 0.0279 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 9/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 40ms/step - loss: 8.5158e-04 - mae: 0.0226 - mse: 8.5158e-04 Epoch 9: val_loss did not improve from 0.00094 Epoch 9: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 24s 46ms/step - loss: 8.5158e-04 - mae: 0.0226 - mse: 8.5158e-04 - val_loss: 0.0013 - val_mae: 0.0280 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 10/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 41ms/step - loss: 8.2657e-04 - mae: 0.0221 - mse: 8.2657e-04 Epoch 10: val_loss improved from 0.00094 to 0.00091, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 24s 47ms/step - loss: 8.2652e-04 - mae: 0.0221 - mse: 8.2652e-04 - val_loss: 9.0895e-04 - val_mae: 0.0233 - val_mse: 9.0895e-04 - learning_rate: 5.0000e-04 Epoch 11/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 8.2025e-04 - mae: 0.0220 - mse: 8.2025e-04 Epoch 11: val_loss improved from 0.00091 to 0.00090, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 8.2022e-04 - mae: 0.0220 - mse: 8.2022e-04 - val_loss: 9.0470e-04 - val_mae: 0.0233 - val_mse: 9.0470e-04 - learning_rate: 5.0000e-04 Epoch 12/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 8.0261e-04 - mae: 0.0218 - mse: 8.0261e-04 Epoch 12: val_loss improved from 0.00090 to 0.00090, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 8.0263e-04 - mae: 0.0218 - mse: 8.0263e-04 - val_loss: 9.0237e-04 - val_mae: 0.0232 - val_mse: 9.0237e-04 - learning_rate: 5.0000e-04 Epoch 13/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.9065e-04 - mae: 0.0216 - mse: 7.9065e-04 Epoch 13: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.9069e-04 - mae: 0.0216 - mse: 7.9069e-04 - val_loss: 9.1270e-04 - val_mae: 0.0234 - val_mse: 9.1270e-04 - learning_rate: 5.0000e-04 Epoch 14/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step - loss: 7.9986e-04 - mae: 0.0218 - mse: 7.9986e-04 Epoch 14: val_loss did not improve from 0.00090 Epoch 14: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 21s 40ms/step - loss: 7.9989e-04 - mae: 0.0218 - mse: 7.9989e-04 - val_loss: 9.0594e-04 - val_mae: 0.0233 - val_mse: 9.0594e-04 - learning_rate: 5.0000e-04 Epoch 15/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.6692e-04 - mae: 0.0213 - mse: 7.6692e-04 Epoch 15: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.6695e-04 - mae: 0.0213 - mse: 7.6695e-04 - val_loss: 9.4888e-04 - val_mae: 0.0237 - val_mse: 9.4888e-04 - learning_rate: 2.5000e-04 Epoch 16/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.8459e-04 - mae: 0.0215 - mse: 7.8459e-04 Epoch 16: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 7.8459e-04 - mae: 0.0215 - mse: 7.8459e-04 - val_loss: 9.5683e-04 - val_mae: 0.0239 - val_mse: 9.5683e-04 - learning_rate: 2.5000e-04 Epoch 17/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.8559e-04 - mae: 0.0215 - mse: 7.8559e-04 Epoch 17: val_loss improved from 0.00090 to 0.00089, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 19s 38ms/step - loss: 7.8556e-04 - mae: 0.0215 - mse: 7.8556e-04 - val_loss: 8.9047e-04 - val_mae: 0.0230 - val_mse: 8.9047e-04 - learning_rate: 2.5000e-04 Epoch 18/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.6350e-04 - mae: 0.0211 - mse: 7.6350e-04 Epoch 18: val_loss improved from 0.00089 to 0.00087, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.6355e-04 - mae: 0.0211 - mse: 7.6355e-04 - val_loss: 8.7059e-04 - val_mae: 0.0228 - val_mse: 8.7059e-04 - learning_rate: 2.5000e-04 Epoch 19/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.8980e-04 - mae: 0.0215 - mse: 7.8980e-04 Epoch 19: val_loss improved from 0.00087 to 0.00086, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 7.8973e-04 - mae: 0.0215 - mse: 7.8973e-04 - val_loss: 8.5952e-04 - val_mae: 0.0226 - val_mse: 8.5952e-04 - learning_rate: 2.5000e-04 Epoch 20/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.6815e-04 - mae: 0.0212 - mse: 7.6815e-04 Epoch 20: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.6816e-04 - mae: 0.0212 - mse: 7.6816e-04 - val_loss: 8.7523e-04 - val_mae: 0.0228 - val_mse: 8.7523e-04 - learning_rate: 2.5000e-04 Epoch 21/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.6488e-04 - mae: 0.0212 - mse: 7.6488e-04 Epoch 21: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.6488e-04 - mae: 0.0212 - mse: 7.6488e-04 - val_loss: 9.1103e-04 - val_mae: 0.0232 - val_mse: 9.1103e-04 - learning_rate: 2.5000e-04 Epoch 22/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 39ms/step - loss: 7.6972e-04 - mae: 0.0212 - mse: 7.6972e-04 Epoch 22: val_loss did not improve from 0.00086 Epoch 22: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814. 517/517 ━━━━━━━━━━━━━━━━━━━━ 23s 45ms/step - loss: 7.6973e-04 - mae: 0.0212 - mse: 7.6973e-04 - val_loss: 8.6403e-04 - val_mae: 0.0227 - val_mse: 8.6403e-04 - learning_rate: 2.5000e-04 Epoch 23/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step - loss: 7.4858e-04 - mae: 0.0209 - mse: 7.4858e-04 Epoch 23: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 21s 40ms/step - loss: 7.4858e-04 - mae: 0.0209 - mse: 7.4858e-04 - val_loss: 8.6655e-04 - val_mae: 0.0227 - val_mse: 8.6655e-04 - learning_rate: 1.2500e-04 Epoch 24/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.4151e-04 - mae: 0.0208 - mse: 7.4151e-04 Epoch 24: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 7.4153e-04 - mae: 0.0208 - mse: 7.4153e-04 - val_loss: 8.6862e-04 - val_mae: 0.0227 - val_mse: 8.6862e-04 - learning_rate: 1.2500e-04 Epoch 25/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.4655e-04 - mae: 0.0209 - mse: 7.4655e-04 Epoch 25: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 7.4653e-04 - mae: 0.0209 - mse: 7.4653e-04 - val_loss: 9.2968e-04 - val_mae: 0.0234 - val_mse: 9.2968e-04 - learning_rate: 1.2500e-04 Epoch 26/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.5604e-04 - mae: 0.0211 - mse: 7.5604e-04 Epoch 26: val_loss improved from 0.00086 to 0.00086, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.5602e-04 - mae: 0.0211 - mse: 7.5602e-04 - val_loss: 8.5505e-04 - val_mae: 0.0225 - val_mse: 8.5505e-04 - learning_rate: 1.2500e-04 Epoch 27/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step - loss: 7.4659e-04 - mae: 0.0209 - mse: 7.4659e-04 Epoch 27: val_loss did not improve from 0.00086 Epoch 27: ReduceLROnPlateau reducing learning rate to 6.25000029685907e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 21s 40ms/step - loss: 7.4657e-04 - mae: 0.0209 - mse: 7.4657e-04 - val_loss: 8.5906e-04 - val_mae: 0.0226 - val_mse: 8.5906e-04 - learning_rate: 1.2500e-04 Epoch 28/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.4403e-04 - mae: 0.0208 - mse: 7.4403e-04 Epoch 28: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 7.4401e-04 - mae: 0.0208 - mse: 7.4401e-04 - val_loss: 8.6235e-04 - val_mae: 0.0226 - val_mse: 8.6235e-04 - learning_rate: 6.2500e-05 Epoch 29/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step - loss: 7.4540e-04 - mae: 0.0209 - mse: 7.4540e-04 Epoch 29: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.4537e-04 - mae: 0.0209 - mse: 7.4537e-04 - val_loss: 8.7100e-04 - val_mae: 0.0227 - val_mse: 8.7100e-04 - learning_rate: 6.2500e-05 Epoch 30/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 38ms/step - loss: 7.3932e-04 - mae: 0.0208 - mse: 7.3932e-04 Epoch 30: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 22s 43ms/step - loss: 7.3931e-04 - mae: 0.0208 - mse: 7.3931e-04 - val_loss: 8.6591e-04 - val_mae: 0.0227 - val_mse: 8.6591e-04 - learning_rate: 6.2500e-05 Epoch 31/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.3090e-04 - mae: 0.0207 - mse: 7.3090e-04 Epoch 31: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 7.3092e-04 - mae: 0.0207 - mse: 7.3092e-04 - val_loss: 9.0777e-04 - val_mae: 0.0231 - val_mse: 9.0777e-04 - learning_rate: 6.2500e-05 Epoch 32/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.3371e-04 - mae: 0.0208 - mse: 7.3371e-04 Epoch 32: val_loss did not improve from 0.00086 Epoch 32: ReduceLROnPlateau reducing learning rate to 3.125000148429535e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 38ms/step - loss: 7.3373e-04 - mae: 0.0208 - mse: 7.3373e-04 - val_loss: 8.6886e-04 - val_mae: 0.0227 - val_mse: 8.6886e-04 - learning_rate: 6.2500e-05 Epoch 33/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.2938e-04 - mae: 0.0207 - mse: 7.2938e-04 Epoch 33: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.2939e-04 - mae: 0.0207 - mse: 7.2939e-04 - val_loss: 8.6503e-04 - val_mae: 0.0226 - val_mse: 8.6503e-04 - learning_rate: 3.1250e-05 Epoch 34/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.3897e-04 - mae: 0.0208 - mse: 7.3897e-04 Epoch 34: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 20s 39ms/step - loss: 7.3895e-04 - mae: 0.0208 - mse: 7.3895e-04 - val_loss: 8.6731e-04 - val_mae: 0.0226 - val_mse: 8.6731e-04 - learning_rate: 3.1250e-05 Epoch 35/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 36ms/step - loss: 7.3332e-04 - mae: 0.0207 - mse: 7.3332e-04 Epoch 35: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 22s 42ms/step - loss: 7.3331e-04 - mae: 0.0207 - mse: 7.3331e-04 - val_loss: 8.7368e-04 - val_mae: 0.0227 - val_mse: 8.7368e-04 - learning_rate: 3.1250e-05 Epoch 36/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 34ms/step - loss: 7.2310e-04 - mae: 0.0207 - mse: 7.2310e-04 Epoch 36: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 21s 40ms/step - loss: 7.2311e-04 - mae: 0.0207 - mse: 7.2311e-04 - val_loss: 8.8018e-04 - val_mae: 0.0228 - val_mse: 8.8018e-04 - learning_rate: 3.1250e-05 Epoch 36: early stopping Restoring model weights from the end of the best epoch: 26.
169/169 ━━━━━━━━━━━━━━━━━━━━ 3s 15ms/step Metric Value 0 MSE 0.001208 1 MAE 0.027549 2 RMSE 0.034753 3 R2 0.283656 4 MAPE 5.342736 5 SMAPE 5.303017 6 SAE 148.405247
Metric Value 0 MSE 0.000515 1 MAE 0.020295 2 RMSE 0.022692 3 R2 -5.076944 4 MAPE 3.552255 5 SMAPE 3.632339 6 SAE 0.405899
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 57ms/step
Registered model 'Direct_LSTM_Model_simple' already exists. Creating a new version of this model... Created version '7' of model 'Direct_LSTM_Model_simple'.
Direct Simple
In [6]:
run_direct_lstm_experiment(
build_direct_lstm_model_simple,
'simple',
'direct_simple',
X_train_dir,
y_train_dir,
X_val_dir,
y_val_dir,
X_test_dir,
y_test_dir,
20,epochs=100,lstm_units=64)
Model: "Direct_LSTM_Model_simple"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_layer (LSTM) │ (None, 64) │ 16,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ output_layer (Dense) │ (None, 20) │ 1,300 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 18,196 (71.08 KB)
Trainable params: 18,196 (71.08 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 0.0342 - mae: 0.0973 - mse: 0.0342 Epoch 1: val_loss improved from inf to 0.00111, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 21ms/step - loss: 0.0340 - mae: 0.0969 - mse: 0.0340 - val_loss: 0.0011 - val_mae: 0.0264 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 2/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 0.0011 - mae: 0.0257 - mse: 0.0011 Epoch 2: val_loss did not improve from 0.00111 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 0.0011 - mae: 0.0257 - mse: 0.0011 - val_loss: 0.0012 - val_mae: 0.0273 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 3/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 0.0011 - mae: 0.0253 - mse: 0.0011 Epoch 3: val_loss improved from 0.00111 to 0.00105, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 0.0011 - mae: 0.0253 - mse: 0.0011 - val_loss: 0.0010 - val_mae: 0.0255 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 4/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 0.0010 - mae: 0.0249 - mse: 0.0010 Epoch 4: val_loss improved from 0.00105 to 0.00102, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 0.0010 - mae: 0.0249 - mse: 0.0010 - val_loss: 0.0010 - val_mae: 0.0252 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 5/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 0.0010 - mae: 0.0247 - mse: 0.0010 Epoch 5: val_loss did not improve from 0.00102 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 0.0010 - mae: 0.0247 - mse: 0.0010 - val_loss: 0.0011 - val_mae: 0.0257 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 6/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 9.3199e-04 - mae: 0.0236 - mse: 9.3199e-04 Epoch 6: val_loss improved from 0.00102 to 0.00095, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.3195e-04 - mae: 0.0236 - mse: 9.3195e-04 - val_loss: 9.4800e-04 - val_mae: 0.0240 - val_mse: 9.4800e-04 - learning_rate: 0.0010 Epoch 7/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.2230e-04 - mae: 0.0233 - mse: 9.2230e-04 Epoch 7: val_loss did not improve from 0.00095 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.2224e-04 - mae: 0.0233 - mse: 9.2224e-04 - val_loss: 0.0016 - val_mae: 0.0324 - val_mse: 0.0016 - learning_rate: 0.0010 Epoch 8/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 20ms/step - loss: 9.0523e-04 - mae: 0.0232 - mse: 9.0523e-04 Epoch 8: val_loss did not improve from 0.00095 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 22ms/step - loss: 9.0511e-04 - mae: 0.0232 - mse: 9.0511e-04 - val_loss: 0.0012 - val_mae: 0.0265 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 9/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 20ms/step - loss: 8.5690e-04 - mae: 0.0226 - mse: 8.5690e-04 Epoch 9: val_loss improved from 0.00095 to 0.00091, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.5685e-04 - mae: 0.0226 - mse: 8.5685e-04 - val_loss: 9.0740e-04 - val_mae: 0.0234 - val_mse: 9.0740e-04 - learning_rate: 0.0010 Epoch 10/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 8.2919e-04 - mae: 0.0222 - mse: 8.2919e-04 Epoch 10: val_loss improved from 0.00091 to 0.00090, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 8.2923e-04 - mae: 0.0222 - mse: 8.2923e-04 - val_loss: 8.9683e-04 - val_mae: 0.0233 - val_mse: 8.9683e-04 - learning_rate: 0.0010 Epoch 11/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 8.7035e-04 - mae: 0.0227 - mse: 8.7035e-04 Epoch 11: val_loss did not improve from 0.00090 Epoch 11: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 8.7019e-04 - mae: 0.0227 - mse: 8.7019e-04 - val_loss: 9.1554e-04 - val_mae: 0.0234 - val_mse: 9.1554e-04 - learning_rate: 0.0010 Epoch 12/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 8.1468e-04 - mae: 0.0218 - mse: 8.1468e-04 Epoch 12: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 8.1462e-04 - mae: 0.0218 - mse: 8.1462e-04 - val_loss: 9.0733e-04 - val_mae: 0.0234 - val_mse: 9.0733e-04 - learning_rate: 5.0000e-04 Epoch 13/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 8.0145e-04 - mae: 0.0217 - mse: 8.0145e-04 Epoch 13: val_loss improved from 0.00090 to 0.00089, saving model to models/saved/Direct_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 8.0142e-04 - mae: 0.0217 - mse: 8.0142e-04 - val_loss: 8.8690e-04 - val_mae: 0.0230 - val_mse: 8.8690e-04 - learning_rate: 5.0000e-04 Epoch 14/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 7.8372e-04 - mae: 0.0215 - mse: 7.8372e-04 Epoch 14: val_loss did not improve from 0.00089 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.8378e-04 - mae: 0.0215 - mse: 7.8378e-04 - val_loss: 8.9812e-04 - val_mae: 0.0233 - val_mse: 8.9812e-04 - learning_rate: 5.0000e-04 Epoch 15/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 8.1153e-04 - mae: 0.0218 - mse: 8.1153e-04 Epoch 15: val_loss did not improve from 0.00089 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 8.1145e-04 - mae: 0.0218 - mse: 8.1145e-04 - val_loss: 9.0741e-04 - val_mae: 0.0235 - val_mse: 9.0741e-04 - learning_rate: 5.0000e-04 Epoch 16/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 7.9464e-04 - mae: 0.0216 - mse: 7.9464e-04 Epoch 16: val_loss did not improve from 0.00089 Epoch 16: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.9463e-04 - mae: 0.0216 - mse: 7.9463e-04 - val_loss: 8.9184e-04 - val_mae: 0.0231 - val_mse: 8.9184e-04 - learning_rate: 5.0000e-04 Epoch 17/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 7.7416e-04 - mae: 0.0213 - mse: 7.7416e-04 Epoch 17: val_loss did not improve from 0.00089 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.7418e-04 - mae: 0.0213 - mse: 7.7418e-04 - val_loss: 9.5578e-04 - val_mae: 0.0238 - val_mse: 9.5578e-04 - learning_rate: 2.5000e-04 Epoch 18/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.6500e-04 - mae: 0.0212 - mse: 7.6500e-04 Epoch 18: val_loss did not improve from 0.00089 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.6508e-04 - mae: 0.0212 - mse: 7.6508e-04 - val_loss: 9.3396e-04 - val_mae: 0.0236 - val_mse: 9.3396e-04 - learning_rate: 2.5000e-04 Epoch 19/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 7.5422e-04 - mae: 0.0211 - mse: 7.5422e-04 Epoch 19: val_loss did not improve from 0.00089 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.5426e-04 - mae: 0.0211 - mse: 7.5426e-04 - val_loss: 8.9908e-04 - val_mae: 0.0231 - val_mse: 8.9908e-04 - learning_rate: 2.5000e-04 Epoch 20/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 20ms/step - loss: 7.7925e-04 - mae: 0.0214 - mse: 7.7925e-04 Epoch 20: val_loss did not improve from 0.00089 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 7.7925e-04 - mae: 0.0214 - mse: 7.7925e-04 - val_loss: 8.9899e-04 - val_mae: 0.0231 - val_mse: 8.9899e-04 - learning_rate: 2.5000e-04 Epoch 21/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 7.6758e-04 - mae: 0.0212 - mse: 7.6758e-04 Epoch 21: val_loss improved from 0.00089 to 0.00086, saving model to models/saved/Direct_LSTM_Model_simple.keras Epoch 21: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814. 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.6759e-04 - mae: 0.0212 - mse: 7.6759e-04 - val_loss: 8.6308e-04 - val_mae: 0.0228 - val_mse: 8.6308e-04 - learning_rate: 2.5000e-04 Epoch 22/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.4762e-04 - mae: 0.0210 - mse: 7.4762e-04 Epoch 22: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 7.4765e-04 - mae: 0.0210 - mse: 7.4765e-04 - val_loss: 9.1741e-04 - val_mae: 0.0233 - val_mse: 9.1741e-04 - learning_rate: 1.2500e-04 Epoch 23/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.6524e-04 - mae: 0.0212 - mse: 7.6524e-04 Epoch 23: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 7.6523e-04 - mae: 0.0212 - mse: 7.6523e-04 - val_loss: 8.8591e-04 - val_mae: 0.0229 - val_mse: 8.8591e-04 - learning_rate: 1.2500e-04 Epoch 24/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.6300e-04 - mae: 0.0212 - mse: 7.6300e-04 Epoch 24: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.6299e-04 - mae: 0.0212 - mse: 7.6299e-04 - val_loss: 9.4335e-04 - val_mae: 0.0236 - val_mse: 9.4335e-04 - learning_rate: 1.2500e-04 Epoch 25/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.5603e-04 - mae: 0.0211 - mse: 7.5603e-04 Epoch 25: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.5605e-04 - mae: 0.0211 - mse: 7.5605e-04 - val_loss: 8.7624e-04 - val_mae: 0.0228 - val_mse: 8.7624e-04 - learning_rate: 1.2500e-04 Epoch 26/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.4723e-04 - mae: 0.0209 - mse: 7.4723e-04 Epoch 26: val_loss did not improve from 0.00086 Epoch 26: ReduceLROnPlateau reducing learning rate to 6.25000029685907e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.4725e-04 - mae: 0.0209 - mse: 7.4725e-04 - val_loss: 9.1245e-04 - val_mae: 0.0232 - val_mse: 9.1245e-04 - learning_rate: 1.2500e-04 Epoch 27/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.4113e-04 - mae: 0.0209 - mse: 7.4113e-04 Epoch 27: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 7.4118e-04 - mae: 0.0209 - mse: 7.4118e-04 - val_loss: 8.8243e-04 - val_mae: 0.0229 - val_mse: 8.8243e-04 - learning_rate: 6.2500e-05 Epoch 28/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.5691e-04 - mae: 0.0210 - mse: 7.5691e-04 Epoch 28: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 7.5690e-04 - mae: 0.0210 - mse: 7.5690e-04 - val_loss: 8.6644e-04 - val_mae: 0.0227 - val_mse: 8.6644e-04 - learning_rate: 6.2500e-05 Epoch 29/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 7.5249e-04 - mae: 0.0210 - mse: 7.5249e-04 Epoch 29: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 7.5250e-04 - mae: 0.0210 - mse: 7.5250e-04 - val_loss: 8.6906e-04 - val_mae: 0.0227 - val_mse: 8.6906e-04 - learning_rate: 6.2500e-05 Epoch 30/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 7.5345e-04 - mae: 0.0210 - mse: 7.5345e-04 Epoch 30: val_loss did not improve from 0.00086 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 7.5344e-04 - mae: 0.0210 - mse: 7.5344e-04 - val_loss: 8.8341e-04 - val_mae: 0.0229 - val_mse: 8.8341e-04 - learning_rate: 6.2500e-05 Epoch 31/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.4741e-04 - mae: 0.0210 - mse: 7.4741e-04 Epoch 31: val_loss did not improve from 0.00086 Epoch 31: ReduceLROnPlateau reducing learning rate to 3.125000148429535e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.4743e-04 - mae: 0.0210 - mse: 7.4743e-04 - val_loss: 8.6847e-04 - val_mae: 0.0228 - val_mse: 8.6847e-04 - learning_rate: 6.2500e-05 Epoch 31: early stopping Restoring model weights from the end of the best epoch: 21.
169/169 ━━━━━━━━━━━━━━━━━━━━ 2s 9ms/step Metric Value 0 MSE 0.001269 1 MAE 0.028276 2 RMSE 0.035626 3 R2 0.247226 4 MAPE 5.398491 5 SMAPE 5.453155 6 SAE 152.324620
Metric Value 0 MSE 0.000675 1 MAE 0.023337 2 RMSE 0.025978 3 R2 -6.964384 4 MAPE 4.087724 5 SMAPE 4.193266 6 SAE 0.466740
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 71ms/step
Registered model 'Direct_LSTM_Model_simple' already exists. Creating a new version of this model... Created version '5' of model 'Direct_LSTM_Model_simple'.
Direct Average 128 units
In [8]:
run_direct_lstm_experiment(
build_direct_model_avg,
'average',
'direct_average',
X_train_dir,
y_train_dir,
X_val_dir,
y_val_dir,
X_test_dir,
y_test_dir,
20,epochs=100,lstm_units=128)
Model: "Avarege_Direct_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional (Bidirectional) │ (None, 100, 512) │ 528,384 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout (Dropout) │ (None, 100, 512) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional_1 (Bidirectional) │ (None, 256) │ 656,384 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_1 (Dropout) │ (None, 256) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense (Dense) │ (None, 128) │ 32,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_2 (Dropout) │ (None, 128) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_1 (Dense) │ (None, 20) │ 2,580 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 1,220,244 (4.65 MB)
Trainable params: 1,220,244 (4.65 MB)
Non-trainable params: 0 (0.00 B)
Epoch 1/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 268ms/step - loss: 0.0196 - mae: 0.0893 - mse: 0.0196 Epoch 1: val_loss improved from inf to 0.00105, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 157s 294ms/step - loss: 0.0196 - mae: 0.0893 - mse: 0.0196 - val_loss: 0.0011 - val_mae: 0.0254 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 2/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 256ms/step - loss: 0.0026 - mae: 0.0398 - mse: 0.0026 Epoch 2: val_loss improved from 0.00105 to 0.00100, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 145s 280ms/step - loss: 0.0026 - mae: 0.0398 - mse: 0.0026 - val_loss: 0.0010 - val_mae: 0.0250 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 3/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 271ms/step - loss: 0.0017 - mae: 0.0330 - mse: 0.0017 Epoch 3: val_loss improved from 0.00100 to 0.00096, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 153s 296ms/step - loss: 0.0017 - mae: 0.0330 - mse: 0.0017 - val_loss: 9.6411e-04 - val_mae: 0.0240 - val_mse: 9.6411e-04 - learning_rate: 0.0010 Epoch 4/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 285ms/step - loss: 0.0015 - mae: 0.0300 - mse: 0.0015 Epoch 4: val_loss improved from 0.00096 to 0.00092, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 162s 314ms/step - loss: 0.0015 - mae: 0.0300 - mse: 0.0015 - val_loss: 9.2012e-04 - val_mae: 0.0237 - val_mse: 9.2012e-04 - learning_rate: 0.0010 Epoch 5/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 286ms/step - loss: 0.0013 - mae: 0.0283 - mse: 0.0013 Epoch 5: val_loss did not improve from 0.00092 517/517 ━━━━━━━━━━━━━━━━━━━━ 162s 314ms/step - loss: 0.0013 - mae: 0.0283 - mse: 0.0013 - val_loss: 0.0010 - val_mae: 0.0246 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 6/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 Epoch 6: val_loss improved from 0.00092 to 0.00087, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 168s 324ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 - val_loss: 8.6523e-04 - val_mae: 0.0228 - val_mse: 8.6523e-04 - learning_rate: 0.0010 Epoch 7/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 288ms/step - loss: 0.0011 - mae: 0.0264 - mse: 0.0011 Epoch 7: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 163s 315ms/step - loss: 0.0011 - mae: 0.0264 - mse: 0.0011 - val_loss: 9.4573e-04 - val_mae: 0.0238 - val_mse: 9.4573e-04 - learning_rate: 0.0010 Epoch 8/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 304ms/step - loss: 0.0011 - mae: 0.0257 - mse: 0.0011 Epoch 8: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 172s 333ms/step - loss: 0.0011 - mae: 0.0257 - mse: 0.0011 - val_loss: 0.0010 - val_mae: 0.0248 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 9/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 291ms/step - loss: 0.0010 - mae: 0.0252 - mse: 0.0010 Epoch 9: val_loss did not improve from 0.00087 Epoch 9: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 166s 321ms/step - loss: 0.0010 - mae: 0.0252 - mse: 0.0010 - val_loss: 8.8997e-04 - val_mae: 0.0231 - val_mse: 8.8997e-04 - learning_rate: 0.0010 Epoch 10/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - loss: 9.5332e-04 - mae: 0.0240 - mse: 9.5332e-04 Epoch 10: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 166s 321ms/step - loss: 9.5331e-04 - mae: 0.0240 - mse: 9.5331e-04 - val_loss: 8.8829e-04 - val_mae: 0.0231 - val_mse: 8.8829e-04 - learning_rate: 5.0000e-04 Epoch 11/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 291ms/step - loss: 9.2466e-04 - mae: 0.0236 - mse: 9.2466e-04 Epoch 11: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 164s 318ms/step - loss: 9.2468e-04 - mae: 0.0236 - mse: 9.2468e-04 - val_loss: 9.2037e-04 - val_mae: 0.0233 - val_mse: 9.2037e-04 - learning_rate: 5.0000e-04 Epoch 12/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 291ms/step - loss: 9.0109e-04 - mae: 0.0233 - mse: 9.0109e-04 Epoch 12: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 165s 319ms/step - loss: 9.0111e-04 - mae: 0.0233 - mse: 9.0111e-04 - val_loss: 9.5016e-04 - val_mae: 0.0236 - val_mse: 9.5016e-04 - learning_rate: 5.0000e-04 Epoch 13/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 290ms/step - loss: 8.9917e-04 - mae: 0.0232 - mse: 8.9917e-04 Epoch 13: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 164s 318ms/step - loss: 8.9917e-04 - mae: 0.0232 - mse: 8.9917e-04 - val_loss: 9.2536e-04 - val_mae: 0.0236 - val_mse: 9.2536e-04 - learning_rate: 5.0000e-04 Epoch 14/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 342ms/step - loss: 8.7548e-04 - mae: 0.0229 - mse: 8.7548e-04 Epoch 14: val_loss did not improve from 0.00087 Epoch 14: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 191s 370ms/step - loss: 8.7550e-04 - mae: 0.0229 - mse: 8.7550e-04 - val_loss: 9.8583e-04 - val_mae: 0.0240 - val_mse: 9.8583e-04 - learning_rate: 5.0000e-04 Epoch 15/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 304ms/step - loss: 8.5721e-04 - mae: 0.0227 - mse: 8.5721e-04 Epoch 15: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 172s 334ms/step - loss: 8.5720e-04 - mae: 0.0227 - mse: 8.5720e-04 - val_loss: 9.5679e-04 - val_mae: 0.0238 - val_mse: 9.5679e-04 - learning_rate: 2.5000e-04 Epoch 16/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 311ms/step - loss: 8.5911e-04 - mae: 0.0226 - mse: 8.5911e-04 Epoch 16: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 176s 341ms/step - loss: 8.5908e-04 - mae: 0.0226 - mse: 8.5908e-04 - val_loss: 0.0010 - val_mae: 0.0243 - val_mse: 0.0010 - learning_rate: 2.5000e-04 Epoch 16: early stopping Restoring model weights from the end of the best epoch: 6.
169/169 ━━━━━━━━━━━━━━━━━━━━ 16s 89ms/step Metric Value 0 MSE 0.001224 1 MAE 0.027700 2 RMSE 0.034987 3 R2 0.273971 4 MAPE 5.360052 5 SMAPE 5.330827 6 SAE 149.217689
Metric Value 0 MSE 0.000144 1 MAE 0.010113 2 RMSE 0.012019 3 R2 -0.704893 4 MAPE 1.767251 5 SMAPE 1.788246 6 SAE 0.202255
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 58ms/step
Registered model 'Direct_LSTM_Model_average' already exists. Creating a new version of this model... Created version '6' of model 'Direct_LSTM_Model_average'.
Direct Average 64 units
In [9]:
run_direct_lstm_experiment(
build_direct_model_avg,
'average',
'direct_average',
X_train_dir,
y_train_dir,
X_val_dir,
y_val_dir,
X_test_dir,
y_test_dir,
20,epochs=100,lstm_units=64)
Model: "Avarege_Direct_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional_2 (Bidirectional) │ (None, 100, 256) │ 133,120 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_3 (Dropout) │ (None, 100, 256) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional_3 (Bidirectional) │ (None, 128) │ 164,352 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_4 (Dropout) │ (None, 128) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_2 (Dense) │ (None, 64) │ 8,256 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_5 (Dropout) │ (None, 64) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_3 (Dense) │ (None, 20) │ 1,300 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 307,028 (1.17 MB)
Trainable params: 307,028 (1.17 MB)
Non-trainable params: 0 (0.00 B)
Epoch 1/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 98ms/step - loss: 0.0304 - mae: 0.1142 - mse: 0.0304 Epoch 1: val_loss improved from inf to 0.00126, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 62s 110ms/step - loss: 0.0303 - mae: 0.1141 - mse: 0.0303 - val_loss: 0.0013 - val_mae: 0.0284 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 2/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 99ms/step - loss: 0.0029 - mae: 0.0425 - mse: 0.0029 Epoch 2: val_loss improved from 0.00126 to 0.00104, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 56s 109ms/step - loss: 0.0029 - mae: 0.0425 - mse: 0.0029 - val_loss: 0.0010 - val_mae: 0.0256 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 3/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 103ms/step - loss: 0.0022 - mae: 0.0368 - mse: 0.0022 Epoch 3: val_loss did not improve from 0.00104 517/517 ━━━━━━━━━━━━━━━━━━━━ 59s 114ms/step - loss: 0.0022 - mae: 0.0368 - mse: 0.0022 - val_loss: 0.0012 - val_mae: 0.0270 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 4/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 101ms/step - loss: 0.0018 - mae: 0.0333 - mse: 0.0018 Epoch 4: val_loss improved from 0.00104 to 0.00101, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 59s 113ms/step - loss: 0.0018 - mae: 0.0333 - mse: 0.0018 - val_loss: 0.0010 - val_mae: 0.0247 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 5/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 108ms/step - loss: 0.0015 - mae: 0.0303 - mse: 0.0015 Epoch 5: val_loss improved from 0.00101 to 0.00096, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 62s 120ms/step - loss: 0.0015 - mae: 0.0303 - mse: 0.0015 - val_loss: 9.5846e-04 - val_mae: 0.0244 - val_mse: 9.5846e-04 - learning_rate: 0.0010 Epoch 6/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 100ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 Epoch 6: val_loss improved from 0.00096 to 0.00090, saving model to models/saved/Direct_LSTM_Model_average.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 58s 112ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 - val_loss: 9.0132e-04 - val_mae: 0.0235 - val_mse: 9.0132e-04 - learning_rate: 0.0010 Epoch 7/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 96ms/step - loss: 0.0012 - mae: 0.0272 - mse: 0.0012 Epoch 7: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 55s 107ms/step - loss: 0.0012 - mae: 0.0272 - mse: 0.0012 - val_loss: 0.0011 - val_mae: 0.0253 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 8/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 100ms/step - loss: 0.0011 - mae: 0.0259 - mse: 0.0011 Epoch 8: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 58s 112ms/step - loss: 0.0011 - mae: 0.0259 - mse: 0.0011 - val_loss: 9.0747e-04 - val_mae: 0.0234 - val_mse: 9.0747e-04 - learning_rate: 0.0010 Epoch 9/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 100ms/step - loss: 0.0010 - mae: 0.0252 - mse: 0.0010 Epoch 9: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 57s 110ms/step - loss: 0.0010 - mae: 0.0252 - mse: 0.0010 - val_loss: 9.5234e-04 - val_mae: 0.0241 - val_mse: 9.5234e-04 - learning_rate: 0.0010 Epoch 10/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 96ms/step - loss: 9.8207e-04 - mae: 0.0245 - mse: 9.8207e-04 Epoch 10: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 55s 107ms/step - loss: 9.8199e-04 - mae: 0.0245 - mse: 9.8199e-04 - val_loss: 0.0010 - val_mae: 0.0247 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 11/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 101ms/step - loss: 9.5536e-04 - mae: 0.0241 - mse: 9.5536e-04 Epoch 11: val_loss did not improve from 0.00090 Epoch 11: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 58s 113ms/step - loss: 9.5530e-04 - mae: 0.0241 - mse: 9.5530e-04 - val_loss: 0.0012 - val_mae: 0.0264 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 12/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 102ms/step - loss: 8.8992e-04 - mae: 0.0231 - mse: 8.8992e-04 Epoch 12: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 59s 113ms/step - loss: 8.8988e-04 - mae: 0.0231 - mse: 8.8988e-04 - val_loss: 0.0013 - val_mae: 0.0277 - val_mse: 0.0013 - learning_rate: 5.0000e-04 Epoch 13/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 97ms/step - loss: 8.6465e-04 - mae: 0.0228 - mse: 8.6465e-04 Epoch 13: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 56s 108ms/step - loss: 8.6465e-04 - mae: 0.0228 - mse: 8.6465e-04 - val_loss: 0.0011 - val_mae: 0.0250 - val_mse: 0.0011 - learning_rate: 5.0000e-04 Epoch 14/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 98ms/step - loss: 8.7316e-04 - mae: 0.0229 - mse: 8.7316e-04 Epoch 14: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 56s 109ms/step - loss: 8.7313e-04 - mae: 0.0229 - mse: 8.7313e-04 - val_loss: 9.9189e-04 - val_mae: 0.0242 - val_mse: 9.9189e-04 - learning_rate: 5.0000e-04 Epoch 15/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 8.4481e-04 - mae: 0.0224 - mse: 8.4481e-04 Epoch 15: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 59s 114ms/step - loss: 8.4483e-04 - mae: 0.0224 - mse: 8.4483e-04 - val_loss: 0.0010 - val_mae: 0.0249 - val_mse: 0.0010 - learning_rate: 5.0000e-04 Epoch 16/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 97ms/step - loss: 8.5512e-04 - mae: 0.0226 - mse: 8.5512e-04 Epoch 16: val_loss did not improve from 0.00090 Epoch 16: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 55s 107ms/step - loss: 8.5507e-04 - mae: 0.0226 - mse: 8.5507e-04 - val_loss: 0.0011 - val_mae: 0.0250 - val_mse: 0.0011 - learning_rate: 5.0000e-04 Epoch 16: early stopping Restoring model weights from the end of the best epoch: 6.
169/169 ━━━━━━━━━━━━━━━━━━━━ 6s 35ms/step Metric Value 0 MSE 0.001281 1 MAE 0.028510 2 RMSE 0.035786 3 R2 0.240445 4 MAPE 5.453953 5 SMAPE 5.502906 6 SAE 153.583266
Metric Value 0 MSE 0.000491 1 MAE 0.020163 2 RMSE 0.022152 3 R2 -4.791197 4 MAPE 3.531630 5 SMAPE 3.607988 6 SAE 0.403259
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 48ms/step
Registered model 'Direct_LSTM_Model_average' already exists. Creating a new version of this model... Created version '7' of model 'Direct_LSTM_Model_average'.
Direct Average 32 units
In [ ]:
run_direct_lstm_experiment(
build_direct_model_avg,
'average',
'direct_average',
X_train_dir,
y_train_dir,
X_val_dir,
y_val_dir,
X_test_dir,
y_test_dir,
20,epochs=100,lstm_units=32)
Model: "Avarege_Direct_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional_4 (Bidirectional) │ (None, 100, 128) │ 33,792 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_6 (Dropout) │ (None, 100, 128) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional_5 (Bidirectional) │ (None, 64) │ 41,216 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_7 (Dropout) │ (None, 64) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_4 (Dense) │ (None, 32) │ 2,080 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_8 (Dropout) │ (None, 32) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_5 (Dense) │ (None, 20) │ 660 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 77,748 (303.70 KB)
Trainable params: 77,748 (303.70 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 109ms/step - loss: 0.0465 - mae: 0.1483 - mse: 0.0465 Epoch 1: val_loss improved from inf to 0.00249, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 69s 123ms/step - loss: 0.0465 - mae: 0.1482 - mse: 0.0465 - val_loss: 0.0025 - val_mae: 0.0422 - val_mse: 0.0025 - learning_rate: 0.0010 Epoch 2/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 107ms/step - loss: 0.0038 - mae: 0.0482 - mse: 0.0038 Epoch 2: val_loss improved from 0.00249 to 0.00146, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 62s 119ms/step - loss: 0.0038 - mae: 0.0482 - mse: 0.0038 - val_loss: 0.0015 - val_mae: 0.0309 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 3/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 106ms/step - loss: 0.0027 - mae: 0.0411 - mse: 0.0027 Epoch 3: val_loss did not improve from 0.00146 516/516 ━━━━━━━━━━━━━━━━━━━━ 61s 118ms/step - loss: 0.0027 - mae: 0.0411 - mse: 0.0027 - val_loss: 0.0026 - val_mae: 0.0436 - val_mse: 0.0026 - learning_rate: 0.0010 Epoch 4/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 106ms/step - loss: 0.0021 - mae: 0.0360 - mse: 0.0021 Epoch 4: val_loss improved from 0.00146 to 0.00141, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 61s 118ms/step - loss: 0.0021 - mae: 0.0360 - mse: 0.0021 - val_loss: 0.0014 - val_mae: 0.0304 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 5/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 107ms/step - loss: 0.0017 - mae: 0.0327 - mse: 0.0017 Epoch 5: val_loss improved from 0.00141 to 0.00099, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 62s 119ms/step - loss: 0.0017 - mae: 0.0327 - mse: 0.0017 - val_loss: 9.8511e-04 - val_mae: 0.0249 - val_mse: 9.8511e-04 - learning_rate: 0.0010 Epoch 6/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 0.0015 - mae: 0.0304 - mse: 0.0015 Epoch 6: val_loss did not improve from 0.00099 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 116ms/step - loss: 0.0015 - mae: 0.0304 - mse: 0.0015 - val_loss: 0.0013 - val_mae: 0.0295 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 7/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 105ms/step - loss: 0.0013 - mae: 0.0283 - mse: 0.0013 Epoch 7: val_loss improved from 0.00099 to 0.00093, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 61s 118ms/step - loss: 0.0013 - mae: 0.0283 - mse: 0.0013 - val_loss: 9.2861e-04 - val_mae: 0.0240 - val_mse: 9.2861e-04 - learning_rate: 0.0010 Epoch 8/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 105ms/step - loss: 0.0012 - mae: 0.0271 - mse: 0.0012 Epoch 8: val_loss did not improve from 0.00093 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 117ms/step - loss: 0.0012 - mae: 0.0271 - mse: 0.0012 - val_loss: 0.0010 - val_mae: 0.0252 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 9/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 0.0011 - mae: 0.0259 - mse: 0.0011 Epoch 9: val_loss did not improve from 0.00093 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 116ms/step - loss: 0.0011 - mae: 0.0259 - mse: 0.0011 - val_loss: 0.0010 - val_mae: 0.0250 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 10/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 0.0011 - mae: 0.0254 - mse: 0.0011 Epoch 10: val_loss did not improve from 0.00093 Epoch 10: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 115ms/step - loss: 0.0011 - mae: 0.0254 - mse: 0.0011 - val_loss: 0.0011 - val_mae: 0.0265 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 11/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 0.0010 - mae: 0.0251 - mse: 0.0010 Epoch 11: val_loss did not improve from 0.00093 516/516 ━━━━━━━━━━━━━━━━━━━━ 59s 115ms/step - loss: 0.0010 - mae: 0.0251 - mse: 0.0010 - val_loss: 0.0010 - val_mae: 0.0253 - val_mse: 0.0010 - learning_rate: 5.0000e-04 Epoch 12/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 101ms/step - loss: 0.0010 - mae: 0.0248 - mse: 0.0010 Epoch 12: val_loss did not improve from 0.00093 516/516 ━━━━━━━━━━━━━━━━━━━━ 58s 113ms/step - loss: 0.0010 - mae: 0.0248 - mse: 0.0010 - val_loss: 9.9758e-04 - val_mae: 0.0247 - val_mse: 9.9758e-04 - learning_rate: 5.0000e-04 Epoch 13/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 106ms/step - loss: 9.8815e-04 - mae: 0.0245 - mse: 9.8815e-04 Epoch 13: val_loss improved from 0.00093 to 0.00090, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 61s 118ms/step - loss: 9.8813e-04 - mae: 0.0245 - mse: 9.8813e-04 - val_loss: 8.9774e-04 - val_mae: 0.0234 - val_mse: 8.9774e-04 - learning_rate: 5.0000e-04 Epoch 14/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 103ms/step - loss: 9.7735e-04 - mae: 0.0244 - mse: 9.7735e-04 Epoch 14: val_loss did not improve from 0.00090 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 116ms/step - loss: 9.7735e-04 - mae: 0.0244 - mse: 9.7735e-04 - val_loss: 0.0012 - val_mae: 0.0273 - val_mse: 0.0012 - learning_rate: 5.0000e-04 Epoch 15/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 103ms/step - loss: 9.7412e-04 - mae: 0.0244 - mse: 9.7412e-04 Epoch 15: val_loss did not improve from 0.00090 Epoch 15: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 516/516 ━━━━━━━━━━━━━━━━━━━━ 59s 115ms/step - loss: 9.7409e-04 - mae: 0.0244 - mse: 9.7409e-04 - val_loss: 0.0011 - val_mae: 0.0257 - val_mse: 0.0011 - learning_rate: 5.0000e-04 Epoch 16/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 102ms/step - loss: 9.5017e-04 - mae: 0.0241 - mse: 9.5017e-04 Epoch 16: val_loss did not improve from 0.00090 516/516 ━━━━━━━━━━━━━━━━━━━━ 59s 114ms/step - loss: 9.5018e-04 - mae: 0.0241 - mse: 9.5018e-04 - val_loss: 0.0010 - val_mae: 0.0249 - val_mse: 0.0010 - learning_rate: 2.5000e-04 Epoch 17/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 9.5148e-04 - mae: 0.0241 - mse: 9.5148e-04 Epoch 17: val_loss did not improve from 0.00090 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 116ms/step - loss: 9.5145e-04 - mae: 0.0241 - mse: 9.5145e-04 - val_loss: 0.0011 - val_mae: 0.0259 - val_mse: 0.0011 - learning_rate: 2.5000e-04 Epoch 18/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 9.2970e-04 - mae: 0.0237 - mse: 9.2970e-04 Epoch 18: val_loss did not improve from 0.00090 516/516 ━━━━━━━━━━━━━━━━━━━━ 59s 115ms/step - loss: 9.2972e-04 - mae: 0.0237 - mse: 9.2972e-04 - val_loss: 9.1160e-04 - val_mae: 0.0235 - val_mse: 9.1160e-04 - learning_rate: 2.5000e-04 Epoch 19/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 102ms/step - loss: 9.3475e-04 - mae: 0.0239 - mse: 9.3475e-04 Epoch 19: val_loss did not improve from 0.00090 516/516 ━━━━━━━━━━━━━━━━━━━━ 59s 113ms/step - loss: 9.3476e-04 - mae: 0.0239 - mse: 9.3476e-04 - val_loss: 0.0010 - val_mae: 0.0248 - val_mse: 0.0010 - learning_rate: 2.5000e-04 Epoch 20/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 101ms/step - loss: 9.3682e-04 - mae: 0.0238 - mse: 9.3682e-04 Epoch 20: val_loss improved from 0.00090 to 0.00087, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 58s 113ms/step - loss: 9.3682e-04 - mae: 0.0238 - mse: 9.3682e-04 - val_loss: 8.7411e-04 - val_mae: 0.0230 - val_mse: 8.7411e-04 - learning_rate: 2.5000e-04 Epoch 21/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 103ms/step - loss: 9.2579e-04 - mae: 0.0237 - mse: 9.2579e-04 Epoch 21: val_loss did not improve from 0.00087 516/516 ━━━━━━━━━━━━━━━━━━━━ 59s 114ms/step - loss: 9.2580e-04 - mae: 0.0237 - mse: 9.2580e-04 - val_loss: 9.4185e-04 - val_mae: 0.0239 - val_mse: 9.4185e-04 - learning_rate: 2.5000e-04 Epoch 22/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 102ms/step - loss: 9.4794e-04 - mae: 0.0240 - mse: 9.4794e-04 Epoch 22: val_loss improved from 0.00087 to 0.00086, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 59s 114ms/step - loss: 9.4792e-04 - mae: 0.0240 - mse: 9.4792e-04 - val_loss: 8.5781e-04 - val_mae: 0.0228 - val_mse: 8.5781e-04 - learning_rate: 2.5000e-04 Epoch 23/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 101ms/step - loss: 9.2239e-04 - mae: 0.0237 - mse: 9.2239e-04 Epoch 23: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 58s 113ms/step - loss: 9.2240e-04 - mae: 0.0237 - mse: 9.2240e-04 - val_loss: 9.1869e-04 - val_mae: 0.0236 - val_mse: 9.1869e-04 - learning_rate: 2.5000e-04 Epoch 24/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 104ms/step - loss: 9.2537e-04 - mae: 0.0237 - mse: 9.2537e-04 Epoch 24: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 115ms/step - loss: 9.2538e-04 - mae: 0.0237 - mse: 9.2538e-04 - val_loss: 9.1946e-04 - val_mae: 0.0236 - val_mse: 9.1946e-04 - learning_rate: 2.5000e-04 Epoch 25/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 105ms/step - loss: 9.2213e-04 - mae: 0.0236 - mse: 9.2213e-04 Epoch 25: val_loss did not improve from 0.00086 Epoch 25: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814. 516/516 ━━━━━━━━━━━━━━━━━━━━ 60s 116ms/step - loss: 9.2214e-04 - mae: 0.0236 - mse: 9.2214e-04 - val_loss: 0.0013 - val_mae: 0.0288 - val_mse: 0.0013 - learning_rate: 2.5000e-04 Epoch 26/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 101ms/step - loss: 9.2896e-04 - mae: 0.0237 - mse: 9.2896e-04 Epoch 26: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 58s 112ms/step - loss: 9.2895e-04 - mae: 0.0237 - mse: 9.2895e-04 - val_loss: 9.8292e-04 - val_mae: 0.0244 - val_mse: 9.8292e-04 - learning_rate: 1.2500e-04 Epoch 27/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 97ms/step - loss: 9.3129e-04 - mae: 0.0237 - mse: 9.3129e-04 Epoch 27: val_loss improved from 0.00086 to 0.00086, saving model to models/saved/Direct_LSTM_Model_average.keras 516/516 ━━━━━━━━━━━━━━━━━━━━ 56s 108ms/step - loss: 9.3127e-04 - mae: 0.0237 - mse: 9.3127e-04 - val_loss: 8.5737e-04 - val_mae: 0.0226 - val_mse: 8.5737e-04 - learning_rate: 1.2500e-04 Epoch 28/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 100ms/step - loss: 9.2187e-04 - mae: 0.0237 - mse: 9.2187e-04 Epoch 28: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 58s 112ms/step - loss: 9.2185e-04 - mae: 0.0237 - mse: 9.2185e-04 - val_loss: 9.1403e-04 - val_mae: 0.0236 - val_mse: 9.1403e-04 - learning_rate: 1.2500e-04 Epoch 29/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 102ms/step - loss: 9.0415e-04 - mae: 0.0234 - mse: 9.0415e-04 Epoch 29: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 58s 113ms/step - loss: 9.0416e-04 - mae: 0.0234 - mse: 9.0416e-04 - val_loss: 8.9964e-04 - val_mae: 0.0233 - val_mse: 8.9964e-04 - learning_rate: 1.2500e-04 Epoch 30/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 99ms/step - loss: 9.2287e-04 - mae: 0.0236 - mse: 9.2287e-04 Epoch 30: val_loss did not improve from 0.00086 Epoch 30: ReduceLROnPlateau reducing learning rate to 6.25000029685907e-05. 516/516 ━━━━━━━━━━━━━━━━━━━━ 57s 110ms/step - loss: 9.2286e-04 - mae: 0.0236 - mse: 9.2286e-04 - val_loss: 9.3180e-04 - val_mae: 0.0238 - val_mse: 9.3180e-04 - learning_rate: 1.2500e-04 Epoch 31/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 98ms/step - loss: 8.9844e-04 - mae: 0.0234 - mse: 8.9844e-04 Epoch 31: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 56s 109ms/step - loss: 8.9845e-04 - mae: 0.0234 - mse: 8.9845e-04 - val_loss: 9.0851e-04 - val_mae: 0.0234 - val_mse: 9.0851e-04 - learning_rate: 6.2500e-05 Epoch 32/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 97ms/step - loss: 8.9819e-04 - mae: 0.0233 - mse: 8.9819e-04 Epoch 32: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 56s 108ms/step - loss: 8.9820e-04 - mae: 0.0233 - mse: 8.9820e-04 - val_loss: 9.0699e-04 - val_mae: 0.0233 - val_mse: 9.0699e-04 - learning_rate: 6.2500e-05 Epoch 33/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 97ms/step - loss: 8.9200e-04 - mae: 0.0232 - mse: 8.9200e-04 Epoch 33: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 56s 108ms/step - loss: 8.9201e-04 - mae: 0.0232 - mse: 8.9201e-04 - val_loss: 8.8171e-04 - val_mae: 0.0230 - val_mse: 8.8171e-04 - learning_rate: 6.2500e-05 Epoch 34/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 97ms/step - loss: 8.8470e-04 - mae: 0.0232 - mse: 8.8470e-04 Epoch 34: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 56s 108ms/step - loss: 8.8473e-04 - mae: 0.0232 - mse: 8.8473e-04 - val_loss: 8.8440e-04 - val_mae: 0.0231 - val_mse: 8.8440e-04 - learning_rate: 6.2500e-05 Epoch 35/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 99ms/step - loss: 8.9359e-04 - mae: 0.0232 - mse: 8.9359e-04 Epoch 35: val_loss did not improve from 0.00086 Epoch 35: ReduceLROnPlateau reducing learning rate to 3.125000148429535e-05. 516/516 ━━━━━━━━━━━━━━━━━━━━ 57s 110ms/step - loss: 8.9360e-04 - mae: 0.0232 - mse: 8.9360e-04 - val_loss: 9.6942e-04 - val_mae: 0.0243 - val_mse: 9.6942e-04 - learning_rate: 6.2500e-05 Epoch 36/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 98ms/step - loss: 8.8090e-04 - mae: 0.0230 - mse: 8.8090e-04 Epoch 36: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 56s 109ms/step - loss: 8.8092e-04 - mae: 0.0230 - mse: 8.8092e-04 - val_loss: 9.2318e-04 - val_mae: 0.0236 - val_mse: 9.2318e-04 - learning_rate: 3.1250e-05 Epoch 37/100 516/516 ━━━━━━━━━━━━━━━━━━━━ 0s 97ms/step - loss: 8.7917e-04 - mae: 0.0231 - mse: 8.7917e-04 Epoch 37: val_loss did not improve from 0.00086 516/516 ━━━━━━━━━━━━━━━━━━━━ 56s 108ms/step - loss: 8.7920e-04 - mae: 0.0231 - mse: 8.7920e-04 - val_loss: 9.0724e-04 - val_mae: 0.0234 - val_mse: 9.0724e-04 - learning_rate: 3.1250e-05 Epoch 37: early stopping Restoring model weights from the end of the best epoch: 27.
169/169 ━━━━━━━━━━━━━━━━━━━━ 6s 35ms/step Metric Value 0 MSE 0.000926 1 MAE 0.023720 2 RMSE 0.030428 3 R2 0.630699 4 MAPE 4.280387 5 SMAPE 4.245939 6 SAE 127.733871
Metric Value 0 MSE 0.001430 1 MAE 0.035124 2 RMSE 0.037815 3 R2 -6.860410 4 MAPE 5.694740 5 SMAPE 5.510978 6 SAE 0.702487
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 41ms/step
Registered model 'Direct_LSTM_Model_average' already exists. Creating a new version of this model... Created version '4' of model 'Direct_LSTM_Model_average'.
Direct Advanced
In [10]:
run_direct_lstm_experiment(
build_advanced_direct_lstm,
'advanced',
'direct_advanced',
X_train_dir,
y_train_dir,
X_val_dir,
y_val_dir,
X_test_dir,
y_test_dir,
20,epochs=100,lstm_units=64)
Model: "Advanced_Direct_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidir_lstm_1 (Bidirectional) │ (None, 100, 128) │ 33,792 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_1 (Dropout) │ (None, 100, 128) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ batch_norm_1 │ (None, 100, 128) │ 512 │ │ (BatchNormalization) │ │ │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_2 (LSTM) │ (None, 32) │ 20,608 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_2 (Dropout) │ (None, 32) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ batch_norm_2 │ (None, 32) │ 128 │ │ (BatchNormalization) │ │ │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_1 (Dense) │ (None, 64) │ 2,112 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_3 (Dropout) │ (None, 64) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_2 (Dense) │ (None, 32) │ 2,080 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ output_layer (Dense) │ (None, 20) │ 660 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 59,892 (233.95 KB)
Trainable params: 59,572 (232.70 KB)
Non-trainable params: 320 (1.25 KB)
Epoch 1/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 56ms/step - loss: 0.1190 - mae: 0.2283 - mse: 0.1190 Epoch 1: val_loss improved from inf to 0.00225, saving model to models/saved/Direct_LSTM_Model_advanced.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 38s 63ms/step - loss: 0.1187 - mae: 0.2279 - mse: 0.1187 - val_loss: 0.0023 - val_mae: 0.0374 - val_mse: 0.0023 - learning_rate: 0.0010 Epoch 2/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 58ms/step - loss: 0.0039 - mae: 0.0490 - mse: 0.0039 Epoch 2: val_loss did not improve from 0.00225 517/517 ━━━━━━━━━━━━━━━━━━━━ 33s 64ms/step - loss: 0.0039 - mae: 0.0490 - mse: 0.0039 - val_loss: 0.0033 - val_mae: 0.0491 - val_mse: 0.0033 - learning_rate: 0.0010 Epoch 3/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 57ms/step - loss: 0.0025 - mae: 0.0392 - mse: 0.0025 Epoch 3: val_loss did not improve from 0.00225 517/517 ━━━━━━━━━━━━━━━━━━━━ 32s 62ms/step - loss: 0.0025 - mae: 0.0392 - mse: 0.0025 - val_loss: 0.0025 - val_mae: 0.0416 - val_mse: 0.0025 - learning_rate: 0.0010 Epoch 4/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 55ms/step - loss: 0.0020 - mae: 0.0348 - mse: 0.0020 Epoch 4: val_loss did not improve from 0.00225 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 60ms/step - loss: 0.0020 - mae: 0.0348 - mse: 0.0020 - val_loss: 0.0025 - val_mae: 0.0412 - val_mse: 0.0025 - learning_rate: 0.0010 Epoch 5/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 51ms/step - loss: 0.0017 - mae: 0.0321 - mse: 0.0017 Epoch 5: val_loss did not improve from 0.00225 517/517 ━━━━━━━━━━━━━━━━━━━━ 30s 57ms/step - loss: 0.0017 - mae: 0.0321 - mse: 0.0017 - val_loss: 0.0033 - val_mae: 0.0472 - val_mse: 0.0033 - learning_rate: 0.0010 Epoch 6/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 52ms/step - loss: 0.0015 - mae: 0.0304 - mse: 0.0015 Epoch 6: val_loss improved from 0.00225 to 0.00136, saving model to models/saved/Direct_LSTM_Model_advanced.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 30s 58ms/step - loss: 0.0015 - mae: 0.0304 - mse: 0.0015 - val_loss: 0.0014 - val_mae: 0.0289 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 7/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 55ms/step - loss: 0.0015 - mae: 0.0301 - mse: 0.0015 Epoch 7: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 60ms/step - loss: 0.0015 - mae: 0.0301 - mse: 0.0015 - val_loss: 0.0015 - val_mae: 0.0306 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 8/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 62ms/step - loss: 0.0014 - mae: 0.0293 - mse: 0.0014 Epoch 8: val_loss improved from 0.00136 to 0.00119, saving model to models/saved/Direct_LSTM_Model_advanced.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 35s 68ms/step - loss: 0.0014 - mae: 0.0293 - mse: 0.0014 - val_loss: 0.0012 - val_mae: 0.0273 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 9/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 56ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 Epoch 9: val_loss did not improve from 0.00119 517/517 ━━━━━━━━━━━━━━━━━━━━ 32s 61ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 - val_loss: 0.0012 - val_mae: 0.0273 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 10/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 Epoch 10: val_loss improved from 0.00119 to 0.00110, saving model to models/saved/Direct_LSTM_Model_advanced.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 60ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 - val_loss: 0.0011 - val_mae: 0.0258 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 11/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step - loss: 0.0012 - mae: 0.0272 - mse: 0.0012 Epoch 11: val_loss did not improve from 0.00110 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 59ms/step - loss: 0.0012 - mae: 0.0272 - mse: 0.0012 - val_loss: 0.0022 - val_mae: 0.0388 - val_mse: 0.0022 - learning_rate: 0.0010 Epoch 12/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 Epoch 12: val_loss did not improve from 0.00110 517/517 ━━━━━━━━━━━━━━━━━━━━ 30s 59ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 - val_loss: 0.0013 - val_mae: 0.0277 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 13/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 56ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 Epoch 13: val_loss improved from 0.00110 to 0.00108, saving model to models/saved/Direct_LSTM_Model_advanced.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 33s 63ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 - val_loss: 0.0011 - val_mae: 0.0259 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 14/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 57ms/step - loss: 0.0011 - mae: 0.0261 - mse: 0.0011 Epoch 14: val_loss did not improve from 0.00108 517/517 ━━━━━━━━━━━━━━━━━━━━ 33s 63ms/step - loss: 0.0011 - mae: 0.0261 - mse: 0.0011 - val_loss: 0.0115 - val_mae: 0.1022 - val_mse: 0.0115 - learning_rate: 0.0010 Epoch 15/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step - loss: 0.0011 - mae: 0.0266 - mse: 0.0011 Epoch 15: val_loss did not improve from 0.00108 517/517 ━━━━━━━━━━━━━━━━━━━━ 30s 59ms/step - loss: 0.0011 - mae: 0.0266 - mse: 0.0011 - val_loss: 0.0011 - val_mae: 0.0259 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 16/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step - loss: 0.0012 - mae: 0.0277 - mse: 0.0012 Epoch 16: val_loss improved from 0.00108 to 0.00103, saving model to models/saved/Direct_LSTM_Model_advanced.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 30s 59ms/step - loss: 0.0012 - mae: 0.0277 - mse: 0.0012 - val_loss: 0.0010 - val_mae: 0.0252 - val_mse: 0.0010 - learning_rate: 0.0010 Epoch 17/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 57ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 Epoch 17: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 32s 62ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 - val_loss: 0.0015 - val_mae: 0.0284 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 18/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 57ms/step - loss: 0.0011 - mae: 0.0262 - mse: 0.0011 Epoch 18: val_loss did not improve from 0.00103 Epoch 18: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 32s 63ms/step - loss: 0.0011 - mae: 0.0262 - mse: 0.0011 - val_loss: 0.0013 - val_mae: 0.0271 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 19/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 61ms/step - loss: 0.0011 - mae: 0.0254 - mse: 0.0011 Epoch 19: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 34s 66ms/step - loss: 0.0011 - mae: 0.0254 - mse: 0.0011 - val_loss: 0.0012 - val_mae: 0.0262 - val_mse: 0.0012 - learning_rate: 5.0000e-04 Epoch 20/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 52ms/step - loss: 0.0010 - mae: 0.0251 - mse: 0.0010 Epoch 20: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 30s 58ms/step - loss: 0.0010 - mae: 0.0251 - mse: 0.0010 - val_loss: 0.0011 - val_mae: 0.0260 - val_mse: 0.0011 - learning_rate: 5.0000e-04 Epoch 21/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step - loss: 0.0010 - mae: 0.0250 - mse: 0.0010 Epoch 21: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 30s 58ms/step - loss: 0.0010 - mae: 0.0250 - mse: 0.0010 - val_loss: 0.0013 - val_mae: 0.0272 - val_mse: 0.0013 - learning_rate: 5.0000e-04 Epoch 22/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 56ms/step - loss: 0.0010 - mae: 0.0250 - mse: 0.0010 Epoch 22: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 61ms/step - loss: 0.0010 - mae: 0.0250 - mse: 0.0010 - val_loss: 0.0013 - val_mae: 0.0277 - val_mse: 0.0013 - learning_rate: 5.0000e-04 Epoch 23/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 55ms/step - loss: 0.0010 - mae: 0.0249 - mse: 0.0010 Epoch 23: val_loss did not improve from 0.00103 Epoch 23: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 61ms/step - loss: 0.0010 - mae: 0.0249 - mse: 0.0010 - val_loss: 0.0010 - val_mae: 0.0256 - val_mse: 0.0010 - learning_rate: 5.0000e-04 Epoch 24/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step - loss: 9.8148e-04 - mae: 0.0245 - mse: 9.8148e-04 Epoch 24: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 60ms/step - loss: 9.8154e-04 - mae: 0.0245 - mse: 9.8154e-04 - val_loss: 0.0011 - val_mae: 0.0264 - val_mse: 0.0011 - learning_rate: 2.5000e-04 Epoch 25/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step - loss: 0.0010 - mae: 0.0248 - mse: 0.0010 Epoch 25: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 31s 59ms/step - loss: 0.0010 - mae: 0.0248 - mse: 0.0010 - val_loss: 0.0012 - val_mae: 0.0265 - val_mse: 0.0012 - learning_rate: 2.5000e-04 Epoch 26/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 52ms/step - loss: 0.0010 - mae: 0.0248 - mse: 0.0010 Epoch 26: val_loss did not improve from 0.00103 517/517 ━━━━━━━━━━━━━━━━━━━━ 29s 57ms/step - loss: 0.0010 - mae: 0.0248 - mse: 0.0010 - val_loss: 0.0012 - val_mae: 0.0268 - val_mse: 0.0012 - learning_rate: 2.5000e-04 Epoch 26: early stopping Restoring model weights from the end of the best epoch: 16.
169/169 ━━━━━━━━━━━━━━━━━━━━ 3s 16ms/step Metric Value 0 MSE 0.001274 1 MAE 0.028266 2 RMSE 0.035700 3 R2 0.244092 4 MAPE 5.437593 5 SMAPE 5.455335 6 SAE 152.266858
Metric Value 0 MSE 0.000785 1 MAE 0.026631 2 RMSE 0.028015 3 R2 -8.262618 4 MAPE 4.674143 5 SMAPE 4.797406 6 SAE 0.532628
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 50ms/step
Registered model 'Direct_LSTM_Model_advanced' already exists. Creating a new version of this model... Created version '4' of model 'Direct_LSTM_Model_advanced'.
Recursive Model
In [11]:
from autoregression.models.RecurLSTM import build_recursive_lstm_simple
Recursive Simple
In [12]:
run_recursive_lstm_experiment(
build_recursive_lstm_simple,
'simple',
'recursive_simple',
X_train_rec,
y_train_rec,
X_val_rec,
y_val_rec,
X_test_rec,
y_test_dir,
n_predicted_rows=5000,
output_steps=20,
epochs=100)
Model: "Recursive_LSTM_Model_simple"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_layer (LSTM) │ (None, 64) │ 16,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ output_layer (Dense) │ (None, 1) │ 65 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 16,961 (66.25 KB)
Trainable params: 16,961 (66.25 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 0.0223 - mae: 0.0677 - mse: 0.0223 Epoch 1: val_loss improved from inf to 0.00041, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 13s 21ms/step - loss: 0.0223 - mae: 0.0676 - mse: 0.0223 - val_loss: 4.0789e-04 - val_mae: 0.0162 - val_mse: 4.0789e-04 - learning_rate: 0.0010 Epoch 2/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 3.7218e-04 - mae: 0.0153 - mse: 3.7218e-04 Epoch 2: val_loss improved from 0.00041 to 0.00030, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 3.7195e-04 - mae: 0.0153 - mse: 3.7195e-04 - val_loss: 2.9547e-04 - val_mae: 0.0138 - val_mse: 2.9547e-04 - learning_rate: 0.0010 Epoch 3/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 2.7518e-04 - mae: 0.0132 - mse: 2.7518e-04 Epoch 3: val_loss improved from 0.00030 to 0.00024, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 2.7509e-04 - mae: 0.0132 - mse: 2.7509e-04 - val_loss: 2.4420e-04 - val_mae: 0.0125 - val_mse: 2.4420e-04 - learning_rate: 0.0010 Epoch 4/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 2.2246e-04 - mae: 0.0118 - mse: 2.2246e-04 Epoch 4: val_loss improved from 0.00024 to 0.00021, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 2.2245e-04 - mae: 0.0118 - mse: 2.2245e-04 - val_loss: 2.1319e-04 - val_mae: 0.0117 - val_mse: 2.1319e-04 - learning_rate: 0.0010 Epoch 5/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.9961e-04 - mae: 0.0112 - mse: 1.9961e-04 Epoch 5: val_loss improved from 0.00021 to 0.00020, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 1.9958e-04 - mae: 0.0112 - mse: 1.9958e-04 - val_loss: 2.0012e-04 - val_mae: 0.0113 - val_mse: 2.0012e-04 - learning_rate: 0.0010 Epoch 6/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.7844e-04 - mae: 0.0106 - mse: 1.7844e-04 Epoch 6: val_loss did not improve from 0.00020 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.7840e-04 - mae: 0.0106 - mse: 1.7840e-04 - val_loss: 2.1538e-04 - val_mae: 0.0118 - val_mse: 2.1538e-04 - learning_rate: 0.0010 Epoch 7/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.5869e-04 - mae: 0.0101 - mse: 1.5869e-04 Epoch 7: val_loss improved from 0.00020 to 0.00017, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 1.5869e-04 - mae: 0.0101 - mse: 1.5869e-04 - val_loss: 1.7083e-04 - val_mae: 0.0105 - val_mse: 1.7083e-04 - learning_rate: 0.0010 Epoch 8/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 1.5451e-04 - mae: 0.0099 - mse: 1.5451e-04 Epoch 8: val_loss improved from 0.00017 to 0.00015, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 1.5451e-04 - mae: 0.0099 - mse: 1.5451e-04 - val_loss: 1.4810e-04 - val_mae: 0.0097 - val_mse: 1.4810e-04 - learning_rate: 0.0010 Epoch 9/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 1.4064e-04 - mae: 0.0094 - mse: 1.4064e-04 Epoch 9: val_loss did not improve from 0.00015 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 1.4063e-04 - mae: 0.0094 - mse: 1.4063e-04 - val_loss: 1.5327e-04 - val_mae: 0.0099 - val_mse: 1.5327e-04 - learning_rate: 0.0010 Epoch 10/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.4202e-04 - mae: 0.0095 - mse: 1.4202e-04 Epoch 10: val_loss improved from 0.00015 to 0.00013, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.4199e-04 - mae: 0.0095 - mse: 1.4199e-04 - val_loss: 1.3404e-04 - val_mae: 0.0092 - val_mse: 1.3404e-04 - learning_rate: 0.0010 Epoch 11/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.3035e-04 - mae: 0.0091 - mse: 1.3035e-04 Epoch 11: val_loss did not improve from 0.00013 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 1.3034e-04 - mae: 0.0091 - mse: 1.3034e-04 - val_loss: 1.3463e-04 - val_mae: 0.0093 - val_mse: 1.3463e-04 - learning_rate: 0.0010 Epoch 12/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 17ms/step - loss: 1.2693e-04 - mae: 0.0090 - mse: 1.2693e-04 Epoch 12: val_loss improved from 0.00013 to 0.00013, saving model to models/saved/Recursive_LSTM_Model_simple.keras Epoch 12: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.2692e-04 - mae: 0.0090 - mse: 1.2692e-04 - val_loss: 1.2675e-04 - val_mae: 0.0090 - val_mse: 1.2675e-04 - learning_rate: 0.0010 Epoch 13/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.1786e-04 - mae: 0.0087 - mse: 1.1786e-04 Epoch 13: val_loss improved from 0.00013 to 0.00012, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 1.1786e-04 - mae: 0.0087 - mse: 1.1786e-04 - val_loss: 1.2396e-04 - val_mae: 0.0089 - val_mse: 1.2396e-04 - learning_rate: 5.0000e-04 Epoch 14/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.1541e-04 - mae: 0.0086 - mse: 1.1541e-04 Epoch 14: val_loss improved from 0.00012 to 0.00012, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 1.1540e-04 - mae: 0.0086 - mse: 1.1540e-04 - val_loss: 1.2016e-04 - val_mae: 0.0087 - val_mse: 1.2016e-04 - learning_rate: 5.0000e-04 Epoch 15/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.1025e-04 - mae: 0.0084 - mse: 1.1025e-04 Epoch 15: val_loss did not improve from 0.00012 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 1.1025e-04 - mae: 0.0084 - mse: 1.1025e-04 - val_loss: 1.2323e-04 - val_mae: 0.0089 - val_mse: 1.2323e-04 - learning_rate: 5.0000e-04 Epoch 16/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.1372e-04 - mae: 0.0085 - mse: 1.1372e-04 Epoch 16: val_loss did not improve from 0.00012 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.1372e-04 - mae: 0.0085 - mse: 1.1372e-04 - val_loss: 1.2122e-04 - val_mae: 0.0088 - val_mse: 1.2122e-04 - learning_rate: 5.0000e-04 Epoch 17/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.0705e-04 - mae: 0.0082 - mse: 1.0705e-04 Epoch 17: val_loss did not improve from 0.00012 Epoch 17: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.0706e-04 - mae: 0.0082 - mse: 1.0706e-04 - val_loss: 1.3296e-04 - val_mae: 0.0092 - val_mse: 1.3296e-04 - learning_rate: 5.0000e-04 Epoch 18/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.0607e-04 - mae: 0.0082 - mse: 1.0607e-04 Epoch 18: val_loss improved from 0.00012 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.0606e-04 - mae: 0.0082 - mse: 1.0606e-04 - val_loss: 1.1347e-04 - val_mae: 0.0085 - val_mse: 1.1347e-04 - learning_rate: 2.5000e-04 Epoch 19/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 17ms/step - loss: 1.0611e-04 - mae: 0.0082 - mse: 1.0611e-04 Epoch 19: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.0611e-04 - mae: 0.0082 - mse: 1.0611e-04 - val_loss: 1.1322e-04 - val_mae: 0.0085 - val_mse: 1.1322e-04 - learning_rate: 2.5000e-04 Epoch 20/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.0342e-04 - mae: 0.0081 - mse: 1.0342e-04 Epoch 20: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.0342e-04 - mae: 0.0081 - mse: 1.0342e-04 - val_loss: 1.1196e-04 - val_mae: 0.0085 - val_mse: 1.1196e-04 - learning_rate: 2.5000e-04 Epoch 21/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.0383e-04 - mae: 0.0081 - mse: 1.0383e-04 Epoch 21: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.0383e-04 - mae: 0.0081 - mse: 1.0383e-04 - val_loss: 1.1070e-04 - val_mae: 0.0084 - val_mse: 1.1070e-04 - learning_rate: 2.5000e-04 Epoch 22/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.0102e-04 - mae: 0.0080 - mse: 1.0102e-04 Epoch 22: val_loss did not improve from 0.00011 Epoch 22: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814. 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.0103e-04 - mae: 0.0080 - mse: 1.0103e-04 - val_loss: 1.1217e-04 - val_mae: 0.0085 - val_mse: 1.1217e-04 - learning_rate: 2.5000e-04 Epoch 23/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.8509e-05 - mae: 0.0079 - mse: 9.8509e-05 Epoch 23: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.8512e-05 - mae: 0.0079 - mse: 9.8512e-05 - val_loss: 1.1473e-04 - val_mae: 0.0086 - val_mse: 1.1473e-04 - learning_rate: 1.2500e-04 Epoch 24/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 9.8208e-05 - mae: 0.0079 - mse: 9.8208e-05 Epoch 24: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 9.8212e-05 - mae: 0.0079 - mse: 9.8212e-05 - val_loss: 1.1186e-04 - val_mae: 0.0085 - val_mse: 1.1186e-04 - learning_rate: 1.2500e-04 Epoch 25/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 1.0005e-04 - mae: 0.0080 - mse: 1.0005e-04 Epoch 25: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 1.0005e-04 - mae: 0.0080 - mse: 1.0005e-04 - val_loss: 1.1116e-04 - val_mae: 0.0084 - val_mse: 1.1116e-04 - learning_rate: 1.2500e-04 Epoch 26/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.9725e-05 - mae: 0.0080 - mse: 9.9725e-05 Epoch 26: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.9724e-05 - mae: 0.0080 - mse: 9.9724e-05 - val_loss: 1.0844e-04 - val_mae: 0.0083 - val_mse: 1.0844e-04 - learning_rate: 1.2500e-04 Epoch 27/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.7593e-05 - mae: 0.0079 - mse: 9.7593e-05 Epoch 27: val_loss did not improve from 0.00011 Epoch 27: ReduceLROnPlateau reducing learning rate to 6.25000029685907e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.7595e-05 - mae: 0.0079 - mse: 9.7595e-05 - val_loss: 1.0853e-04 - val_mae: 0.0084 - val_mse: 1.0853e-04 - learning_rate: 1.2500e-04 Epoch 28/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6563e-05 - mae: 0.0079 - mse: 9.6563e-05 Epoch 28: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 9.6569e-05 - mae: 0.0079 - mse: 9.6569e-05 - val_loss: 1.0805e-04 - val_mae: 0.0083 - val_mse: 1.0805e-04 - learning_rate: 6.2500e-05 Epoch 29/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6493e-05 - mae: 0.0079 - mse: 9.6493e-05 Epoch 29: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.6496e-05 - mae: 0.0079 - mse: 9.6496e-05 - val_loss: 1.0768e-04 - val_mae: 0.0083 - val_mse: 1.0768e-04 - learning_rate: 6.2500e-05 Epoch 30/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6786e-05 - mae: 0.0079 - mse: 9.6786e-05 Epoch 30: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 9.6790e-05 - mae: 0.0079 - mse: 9.6790e-05 - val_loss: 1.0787e-04 - val_mae: 0.0083 - val_mse: 1.0787e-04 - learning_rate: 6.2500e-05 Epoch 31/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6261e-05 - mae: 0.0078 - mse: 9.6261e-05 Epoch 31: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 9.6266e-05 - mae: 0.0078 - mse: 9.6266e-05 - val_loss: 1.0720e-04 - val_mae: 0.0083 - val_mse: 1.0720e-04 - learning_rate: 6.2500e-05 Epoch 32/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 9.7658e-05 - mae: 0.0079 - mse: 9.7658e-05 Epoch 32: val_loss did not improve from 0.00011 Epoch 32: ReduceLROnPlateau reducing learning rate to 3.125000148429535e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.7655e-05 - mae: 0.0079 - mse: 9.7655e-05 - val_loss: 1.0767e-04 - val_mae: 0.0083 - val_mse: 1.0767e-04 - learning_rate: 6.2500e-05 Epoch 33/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.8006e-05 - mae: 0.0079 - mse: 9.8006e-05 Epoch 33: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 9.7994e-05 - mae: 0.0079 - mse: 9.7994e-05 - val_loss: 1.0774e-04 - val_mae: 0.0083 - val_mse: 1.0774e-04 - learning_rate: 3.1250e-05 Epoch 34/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6265e-05 - mae: 0.0078 - mse: 9.6265e-05 Epoch 34: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.6264e-05 - mae: 0.0078 - mse: 9.6264e-05 - val_loss: 1.1063e-04 - val_mae: 0.0084 - val_mse: 1.1063e-04 - learning_rate: 3.1250e-05 Epoch 35/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6135e-05 - mae: 0.0078 - mse: 9.6135e-05 Epoch 35: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.6134e-05 - mae: 0.0078 - mse: 9.6134e-05 - val_loss: 1.0735e-04 - val_mae: 0.0083 - val_mse: 1.0735e-04 - learning_rate: 3.1250e-05 Epoch 36/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.5114e-05 - mae: 0.0078 - mse: 9.5114e-05 Epoch 36: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 9.5119e-05 - mae: 0.0078 - mse: 9.5119e-05 - val_loss: 1.0743e-04 - val_mae: 0.0083 - val_mse: 1.0743e-04 - learning_rate: 3.1250e-05 Epoch 37/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6961e-05 - mae: 0.0079 - mse: 9.6961e-05 Epoch 37: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras Epoch 37: ReduceLROnPlateau reducing learning rate to 1.5625000742147677e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.6958e-05 - mae: 0.0079 - mse: 9.6958e-05 - val_loss: 1.0706e-04 - val_mae: 0.0083 - val_mse: 1.0706e-04 - learning_rate: 3.1250e-05 Epoch 38/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.7428e-05 - mae: 0.0079 - mse: 9.7428e-05 Epoch 38: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.7421e-05 - mae: 0.0079 - mse: 9.7421e-05 - val_loss: 1.0671e-04 - val_mae: 0.0083 - val_mse: 1.0671e-04 - learning_rate: 1.5625e-05 Epoch 39/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 9.6065e-05 - mae: 0.0078 - mse: 9.6065e-05 Epoch 39: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 9.6064e-05 - mae: 0.0078 - mse: 9.6064e-05 - val_loss: 1.0655e-04 - val_mae: 0.0083 - val_mse: 1.0655e-04 - learning_rate: 1.5625e-05 Epoch 40/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.5351e-05 - mae: 0.0078 - mse: 9.5351e-05 Epoch 40: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.5352e-05 - mae: 0.0078 - mse: 9.5352e-05 - val_loss: 1.0651e-04 - val_mae: 0.0083 - val_mse: 1.0651e-04 - learning_rate: 1.5625e-05 Epoch 41/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 17ms/step - loss: 9.4426e-05 - mae: 0.0078 - mse: 9.4426e-05 Epoch 41: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.4431e-05 - mae: 0.0078 - mse: 9.4431e-05 - val_loss: 1.0644e-04 - val_mae: 0.0083 - val_mse: 1.0644e-04 - learning_rate: 1.5625e-05 Epoch 42/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.5411e-05 - mae: 0.0078 - mse: 9.5411e-05 Epoch 42: val_loss did not improve from 0.00011 Epoch 42: ReduceLROnPlateau reducing learning rate to 7.812500371073838e-06. 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.5413e-05 - mae: 0.0078 - mse: 9.5413e-05 - val_loss: 1.0647e-04 - val_mae: 0.0083 - val_mse: 1.0647e-04 - learning_rate: 1.5625e-05 Epoch 43/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 17ms/step - loss: 9.4322e-05 - mae: 0.0077 - mse: 9.4322e-05 Epoch 43: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 19ms/step - loss: 9.4327e-05 - mae: 0.0077 - mse: 9.4327e-05 - val_loss: 1.0644e-04 - val_mae: 0.0083 - val_mse: 1.0644e-04 - learning_rate: 7.8125e-06 Epoch 44/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 17ms/step - loss: 9.5733e-05 - mae: 0.0078 - mse: 9.5733e-05 Epoch 44: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.5730e-05 - mae: 0.0078 - mse: 9.5730e-05 - val_loss: 1.0672e-04 - val_mae: 0.0083 - val_mse: 1.0672e-04 - learning_rate: 7.8125e-06 Epoch 45/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.5645e-05 - mae: 0.0078 - mse: 9.5645e-05 Epoch 45: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.5644e-05 - mae: 0.0078 - mse: 9.5644e-05 - val_loss: 1.0646e-04 - val_mae: 0.0083 - val_mse: 1.0646e-04 - learning_rate: 7.8125e-06 Epoch 46/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 17ms/step - loss: 9.5876e-05 - mae: 0.0078 - mse: 9.5876e-05 Epoch 46: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.5874e-05 - mae: 0.0078 - mse: 9.5874e-05 - val_loss: 1.0639e-04 - val_mae: 0.0083 - val_mse: 1.0639e-04 - learning_rate: 7.8125e-06 Epoch 47/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.4953e-05 - mae: 0.0078 - mse: 9.4953e-05 Epoch 47: val_loss did not improve from 0.00011 Epoch 47: ReduceLROnPlateau reducing learning rate to 3.906250185536919e-06. 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.4955e-05 - mae: 0.0078 - mse: 9.4955e-05 - val_loss: 1.0695e-04 - val_mae: 0.0083 - val_mse: 1.0695e-04 - learning_rate: 7.8125e-06 Epoch 48/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.5919e-05 - mae: 0.0078 - mse: 9.5919e-05 Epoch 48: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.5916e-05 - mae: 0.0078 - mse: 9.5916e-05 - val_loss: 1.0703e-04 - val_mae: 0.0083 - val_mse: 1.0703e-04 - learning_rate: 3.9063e-06 Epoch 49/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 9.6054e-05 - mae: 0.0078 - mse: 9.6054e-05 Epoch 49: val_loss improved from 0.00011 to 0.00011, saving model to models/saved/Recursive_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.6047e-05 - mae: 0.0078 - mse: 9.6047e-05 - val_loss: 1.0637e-04 - val_mae: 0.0083 - val_mse: 1.0637e-04 - learning_rate: 3.9063e-06 Epoch 50/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.4073e-05 - mae: 0.0077 - mse: 9.4073e-05 Epoch 50: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 9.4075e-05 - mae: 0.0077 - mse: 9.4075e-05 - val_loss: 1.0663e-04 - val_mae: 0.0083 - val_mse: 1.0663e-04 - learning_rate: 3.9063e-06 Epoch 51/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.5766e-05 - mae: 0.0078 - mse: 9.5766e-05 Epoch 51: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.5764e-05 - mae: 0.0078 - mse: 9.5764e-05 - val_loss: 1.0713e-04 - val_mae: 0.0083 - val_mse: 1.0713e-04 - learning_rate: 3.9063e-06 Epoch 52/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.4190e-05 - mae: 0.0077 - mse: 9.4190e-05 Epoch 52: val_loss did not improve from 0.00011 Epoch 52: ReduceLROnPlateau reducing learning rate to 1.9531250927684596e-06. 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.4194e-05 - mae: 0.0077 - mse: 9.4194e-05 - val_loss: 1.0657e-04 - val_mae: 0.0083 - val_mse: 1.0657e-04 - learning_rate: 3.9063e-06 Epoch 53/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.3605e-05 - mae: 0.0077 - mse: 9.3605e-05 Epoch 53: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 21ms/step - loss: 9.3616e-05 - mae: 0.0077 - mse: 9.3616e-05 - val_loss: 1.0642e-04 - val_mae: 0.0083 - val_mse: 1.0642e-04 - learning_rate: 1.9531e-06 Epoch 54/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 9.6145e-05 - mae: 0.0079 - mse: 9.6145e-05 Epoch 54: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 9.6143e-05 - mae: 0.0079 - mse: 9.6143e-05 - val_loss: 1.0640e-04 - val_mae: 0.0083 - val_mse: 1.0640e-04 - learning_rate: 1.9531e-06 Epoch 55/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 19ms/step - loss: 9.5162e-05 - mae: 0.0078 - mse: 9.5162e-05 Epoch 55: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 22ms/step - loss: 9.5161e-05 - mae: 0.0078 - mse: 9.5161e-05 - val_loss: 1.0643e-04 - val_mae: 0.0083 - val_mse: 1.0643e-04 - learning_rate: 1.9531e-06 Epoch 56/100 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.6340e-05 - mae: 0.0078 - mse: 9.6340e-05 Epoch 56: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 20ms/step - loss: 9.6335e-05 - mae: 0.0078 - mse: 9.6335e-05 - val_loss: 1.0656e-04 - val_mae: 0.0083 - val_mse: 1.0656e-04 - learning_rate: 1.9531e-06 Epoch 57/100 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 17ms/step - loss: 9.3656e-05 - mae: 0.0077 - mse: 9.3656e-05 Epoch 57: val_loss did not improve from 0.00011 Epoch 57: ReduceLROnPlateau reducing learning rate to 1e-06. 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.3667e-05 - mae: 0.0077 - mse: 9.3667e-05 - val_loss: 1.0648e-04 - val_mae: 0.0083 - val_mse: 1.0648e-04 - learning_rate: 1.9531e-06 Epoch 58/100 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.3052e-05 - mae: 0.0077 - mse: 9.3052e-05 Epoch 58: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.3064e-05 - mae: 0.0077 - mse: 9.3064e-05 - val_loss: 1.0645e-04 - val_mae: 0.0083 - val_mse: 1.0645e-04 - learning_rate: 1.0000e-06 Epoch 59/100 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 18ms/step - loss: 9.7913e-05 - mae: 0.0079 - mse: 9.7913e-05 Epoch 59: val_loss did not improve from 0.00011 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 20ms/step - loss: 9.7907e-05 - mae: 0.0079 - mse: 9.7907e-05 - val_loss: 1.0653e-04 - val_mae: 0.0083 - val_mse: 1.0653e-04 - learning_rate: 1.0000e-06 Epoch 59: early stopping Restoring model weights from the end of the best epoch: 49.
Metric Value 0 MSE 0.001243 1 MAE 0.027941 2 RMSE 0.035250 3 R2 0.257703 4 MAPE 5.413987 5 SMAPE 5.404641 6 SAE 139.702630
Metric Value 0 MSE 0.000485 1 MAE 0.019264 2 RMSE 0.022012 3 R2 -4.718252 4 MAPE 3.369496 5 SMAPE 3.444757 6 SAE 0.385276
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 36ms/step
Registered model 'Recursive_LSTM_Model_simple' already exists. Creating a new version of this model... Created version '2' of model 'Recursive_LSTM_Model_simple'.
Sequence to sequence model
In [13]:
from autoregression.utils_ar import run_seq2seq_lstm_experiment
from autoregression.models.seq2seq_lstm import build_seq2seq_lstm_simple
Seq2Seq Simple
In [14]:
run_seq2seq_lstm_experiment(build_seq2seq_lstm_simple,
'simple',
'seq2seq_simple',
X_train=X_train_dir,
X_test=X_test_dir,
X_val=X_val_dir,
y_test=y_test_dir,
y_train=y_train_dir,
y_val=y_val_dir,
output_steps=20,
lstm_units=32)
Model: "Seq2Seq_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ encoder_input (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ encoder_lstm (LSTM) │ (None, 32) │ 4,352 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ repeat_vector (RepeatVector) │ (None, 20, 32) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ decoder_lstm (LSTM) │ (None, 20, 32) │ 8,320 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ time_distributed_output │ (None, 20, 1) │ 33 │ │ (TimeDistributed) │ │ │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 12,705 (49.63 KB)
Trainable params: 12,705 (49.63 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 20ms/step - loss: 0.0313 - mae: 0.1024 - mse: 0.0313 Epoch 1: val_loss improved from inf to 0.00211, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 15s 23ms/step - loss: 0.0312 - mae: 0.1021 - mse: 0.0312 - val_loss: 0.0021 - val_mae: 0.0372 - val_mse: 0.0021 - learning_rate: 0.0010 Epoch 2/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 0.0011 - mae: 0.0259 - mse: 0.0011 Epoch 2: val_loss improved from 0.00211 to 0.00113, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 0.0011 - mae: 0.0259 - mse: 0.0011 - val_loss: 0.0011 - val_mae: 0.0268 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 3/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 0.0011 - mae: 0.0255 - mse: 0.0011 Epoch 3: val_loss improved from 0.00113 to 0.00112, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 0.0011 - mae: 0.0255 - mse: 0.0011 - val_loss: 0.0011 - val_mae: 0.0267 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 4/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 22ms/step - loss: 0.0010 - mae: 0.0250 - mse: 0.0010 Epoch 4: val_loss did not improve from 0.00112 517/517 ━━━━━━━━━━━━━━━━━━━━ 13s 24ms/step - loss: 0.0010 - mae: 0.0250 - mse: 0.0010 - val_loss: 0.0012 - val_mae: 0.0279 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 5/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 22ms/step - loss: 9.9728e-04 - mae: 0.0246 - mse: 9.9728e-04 Epoch 5: val_loss did not improve from 0.00112 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 24ms/step - loss: 9.9728e-04 - mae: 0.0246 - mse: 9.9728e-04 - val_loss: 0.0012 - val_mae: 0.0272 - val_mse: 0.0012 - learning_rate: 0.0010 Epoch 6/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 20ms/step - loss: 9.8188e-04 - mae: 0.0244 - mse: 9.8188e-04 Epoch 6: val_loss improved from 0.00112 to 0.00109, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 22ms/step - loss: 9.8177e-04 - mae: 0.0244 - mse: 9.8177e-04 - val_loss: 0.0011 - val_mae: 0.0261 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 7/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 9.4655e-04 - mae: 0.0240 - mse: 9.4655e-04 Epoch 7: val_loss improved from 0.00109 to 0.00106, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras Epoch 7: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 24ms/step - loss: 9.4653e-04 - mae: 0.0240 - mse: 9.4653e-04 - val_loss: 0.0011 - val_mae: 0.0256 - val_mse: 0.0011 - learning_rate: 0.0010 Epoch 8/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 23ms/step - loss: 8.7916e-04 - mae: 0.0230 - mse: 8.7916e-04 Epoch 8: val_loss improved from 0.00106 to 0.00104, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 14s 27ms/step - loss: 8.7917e-04 - mae: 0.0230 - mse: 8.7917e-04 - val_loss: 0.0010 - val_mae: 0.0253 - val_mse: 0.0010 - learning_rate: 5.0000e-04 Epoch 9/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.7363e-04 - mae: 0.0229 - mse: 8.7363e-04 Epoch 9: val_loss improved from 0.00104 to 0.00094, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.7363e-04 - mae: 0.0229 - mse: 8.7363e-04 - val_loss: 9.4490e-04 - val_mae: 0.0242 - val_mse: 9.4490e-04 - learning_rate: 5.0000e-04 Epoch 10/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.4838e-04 - mae: 0.0225 - mse: 8.4838e-04 Epoch 10: val_loss did not improve from 0.00094 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.4838e-04 - mae: 0.0225 - mse: 8.4838e-04 - val_loss: 9.7144e-04 - val_mae: 0.0246 - val_mse: 9.7144e-04 - learning_rate: 5.0000e-04 Epoch 11/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.6579e-04 - mae: 0.0228 - mse: 8.6579e-04 Epoch 11: val_loss did not improve from 0.00094 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 24ms/step - loss: 8.6580e-04 - mae: 0.0228 - mse: 8.6580e-04 - val_loss: 0.0011 - val_mae: 0.0256 - val_mse: 0.0011 - learning_rate: 5.0000e-04 Epoch 12/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.4321e-04 - mae: 0.0224 - mse: 8.4321e-04 Epoch 12: val_loss improved from 0.00094 to 0.00091, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.4316e-04 - mae: 0.0224 - mse: 8.4316e-04 - val_loss: 9.1169e-04 - val_mae: 0.0236 - val_mse: 9.1169e-04 - learning_rate: 5.0000e-04 Epoch 13/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.3097e-04 - mae: 0.0223 - mse: 8.3097e-04 Epoch 13: val_loss improved from 0.00091 to 0.00090, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.3097e-04 - mae: 0.0223 - mse: 8.3097e-04 - val_loss: 8.9893e-04 - val_mae: 0.0234 - val_mse: 8.9893e-04 - learning_rate: 5.0000e-04 Epoch 14/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.4701e-04 - mae: 0.0225 - mse: 8.4701e-04 Epoch 14: val_loss did not improve from 0.00090 Epoch 14: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.4698e-04 - mae: 0.0225 - mse: 8.4698e-04 - val_loss: 9.2073e-04 - val_mae: 0.0237 - val_mse: 9.2073e-04 - learning_rate: 5.0000e-04 Epoch 15/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.0233e-04 - mae: 0.0218 - mse: 8.0233e-04 Epoch 15: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.0233e-04 - mae: 0.0218 - mse: 8.0233e-04 - val_loss: 9.0221e-04 - val_mae: 0.0233 - val_mse: 9.0221e-04 - learning_rate: 2.5000e-04 Epoch 16/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 22ms/step - loss: 7.8455e-04 - mae: 0.0215 - mse: 7.8455e-04 Epoch 16: val_loss did not improve from 0.00090 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.8455e-04 - mae: 0.0215 - mse: 7.8455e-04 - val_loss: 9.2623e-04 - val_mae: 0.0235 - val_mse: 9.2623e-04 - learning_rate: 2.5000e-04 Epoch 17/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 22ms/step - loss: 7.9581e-04 - mae: 0.0217 - mse: 7.9581e-04 Epoch 17: val_loss improved from 0.00090 to 0.00088, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 13s 25ms/step - loss: 7.9580e-04 - mae: 0.0217 - mse: 7.9580e-04 - val_loss: 8.7857e-04 - val_mae: 0.0231 - val_mse: 8.7857e-04 - learning_rate: 2.5000e-04 Epoch 18/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 23ms/step - loss: 7.8464e-04 - mae: 0.0216 - mse: 7.8464e-04 Epoch 18: val_loss did not improve from 0.00088 517/517 ━━━━━━━━━━━━━━━━━━━━ 13s 25ms/step - loss: 7.8466e-04 - mae: 0.0216 - mse: 7.8466e-04 - val_loss: 8.8923e-04 - val_mae: 0.0231 - val_mse: 8.8923e-04 - learning_rate: 2.5000e-04 Epoch 19/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 8.0185e-04 - mae: 0.0218 - mse: 8.0185e-04 Epoch 19: val_loss improved from 0.00088 to 0.00088, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras Epoch 19: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814. 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 8.0177e-04 - mae: 0.0218 - mse: 8.0177e-04 - val_loss: 8.7705e-04 - val_mae: 0.0230 - val_mse: 8.7705e-04 - learning_rate: 2.5000e-04 Epoch 20/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.6452e-04 - mae: 0.0213 - mse: 7.6452e-04 Epoch 20: val_loss did not improve from 0.00088 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.6453e-04 - mae: 0.0213 - mse: 7.6453e-04 - val_loss: 9.2464e-04 - val_mae: 0.0235 - val_mse: 9.2464e-04 - learning_rate: 1.2500e-04 Epoch 21/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.6854e-04 - mae: 0.0213 - mse: 7.6854e-04 Epoch 21: val_loss improved from 0.00088 to 0.00088, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.6856e-04 - mae: 0.0213 - mse: 7.6856e-04 - val_loss: 8.7571e-04 - val_mae: 0.0230 - val_mse: 8.7571e-04 - learning_rate: 1.2500e-04 Epoch 22/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.6769e-04 - mae: 0.0213 - mse: 7.6769e-04 Epoch 22: val_loss did not improve from 0.00088 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.6766e-04 - mae: 0.0213 - mse: 7.6766e-04 - val_loss: 8.8264e-04 - val_mae: 0.0230 - val_mse: 8.8264e-04 - learning_rate: 1.2500e-04 Epoch 23/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.6507e-04 - mae: 0.0213 - mse: 7.6507e-04 Epoch 23: val_loss improved from 0.00088 to 0.00087, saving model to models/saved/Seq2seq_LSTM_Model_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.6507e-04 - mae: 0.0213 - mse: 7.6507e-04 - val_loss: 8.6759e-04 - val_mae: 0.0229 - val_mse: 8.6759e-04 - learning_rate: 1.2500e-04 Epoch 24/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.7070e-04 - mae: 0.0214 - mse: 7.7070e-04 Epoch 24: val_loss did not improve from 0.00087 Epoch 24: ReduceLROnPlateau reducing learning rate to 6.25000029685907e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 22ms/step - loss: 7.7069e-04 - mae: 0.0214 - mse: 7.7069e-04 - val_loss: 9.0209e-04 - val_mae: 0.0233 - val_mse: 9.0209e-04 - learning_rate: 1.2500e-04 Epoch 25/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 20ms/step - loss: 7.4926e-04 - mae: 0.0210 - mse: 7.4926e-04 Epoch 25: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 22ms/step - loss: 7.4928e-04 - mae: 0.0210 - mse: 7.4928e-04 - val_loss: 8.8213e-04 - val_mae: 0.0230 - val_mse: 8.8213e-04 - learning_rate: 6.2500e-05 Epoch 26/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.5519e-04 - mae: 0.0212 - mse: 7.5519e-04 Epoch 26: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 24ms/step - loss: 7.5517e-04 - mae: 0.0212 - mse: 7.5517e-04 - val_loss: 9.1151e-04 - val_mae: 0.0233 - val_mse: 9.1151e-04 - learning_rate: 6.2500e-05 Epoch 27/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.5492e-04 - mae: 0.0211 - mse: 7.5492e-04 Epoch 27: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.5492e-04 - mae: 0.0211 - mse: 7.5492e-04 - val_loss: 8.7777e-04 - val_mae: 0.0229 - val_mse: 8.7777e-04 - learning_rate: 6.2500e-05 Epoch 28/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.5484e-04 - mae: 0.0211 - mse: 7.5484e-04 Epoch 28: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.5482e-04 - mae: 0.0211 - mse: 7.5482e-04 - val_loss: 8.7924e-04 - val_mae: 0.0230 - val_mse: 8.7924e-04 - learning_rate: 6.2500e-05 Epoch 29/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 21ms/step - loss: 7.7054e-04 - mae: 0.0213 - mse: 7.7054e-04 Epoch 29: val_loss did not improve from 0.00087 Epoch 29: ReduceLROnPlateau reducing learning rate to 3.125000148429535e-05. 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 23ms/step - loss: 7.7048e-04 - mae: 0.0213 - mse: 7.7048e-04 - val_loss: 8.8402e-04 - val_mae: 0.0230 - val_mse: 8.8402e-04 - learning_rate: 6.2500e-05 Epoch 30/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 22ms/step - loss: 7.4348e-04 - mae: 0.0210 - mse: 7.4348e-04 Epoch 30: val_loss did not improve from 0.00087 517/517 ━━━━━━━━━━━━━━━━━━━━ 12s 24ms/step - loss: 7.4349e-04 - mae: 0.0210 - mse: 7.4349e-04 - val_loss: 8.9514e-04 - val_mae: 0.0231 - val_mse: 8.9514e-04 - learning_rate: 3.1250e-05 Restoring model weights from the end of the best epoch: 23.
169/169 ━━━━━━━━━━━━━━━━━━━━ 2s 10ms/step Metric Value 0 MSE 0.001281 1 MAE 0.028396 2 RMSE 0.035788 3 R2 0.240361 4 MAPE 5.439545 5 SMAPE 5.473669 6 SAE 152.969791
Metric Value 0 MSE 0.000742 1 MAE 0.024732 2 RMSE 0.027235 3 R2 -7.753836 4 MAPE 4.333463 5 SMAPE 4.449644 6 SAE 0.494634
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 62ms/step
Registered model 'Seq2seq_LSTM_Model_simple' already exists. Creating a new version of this model... Created version '4' of model 'Seq2seq_LSTM_Model_simple'.
Hybrid Model
In [5]:
from autoregression.utils_ar import run_direct_refiner_experiment
from autoregression.models.RefineLSTM import build_refinement_cnn_model_simple,build_refinement_lstm_model_simple,build_average_refinement_lstm
import mlflow.keras
Hybrid: Direct Simple + Refine LSTM Simple
In [21]:
dir_model = mlflow.keras.load_model("models:/Direct_LSTM_Model_simple/7")
run_direct_refiner_experiment(build_refinement_lstm_model_simple,
dir_model,
'simple_lstm_simple',
'ref_simple_lstm_simple',
X_train_dir=X_train_dir,
X_test_dir=X_test_dir,
X_val_dir=X_val_dir,
y_test_dir=y_test_dir,
y_train_dir=y_train_dir,
y_val_dir=y_val_dir,
output_steps=20,
units=64)
517/517 ━━━━━━━━━━━━━━━━━━━━ 9s 18ms/step 173/173 ━━━━━━━━━━━━━━━━━━━━ 3s 16ms/step 169/169 ━━━━━━━━━━━━━━━━━━━━ 3s 17ms/step (20, 1)
Model: "Refinement_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ refinement_input (InputLayer) │ (None, 20, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ refinement_lstm (LSTM) │ (None, 64) │ 16,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ refined_20th_output (Dense) │ (None, 1) │ 65 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 16,961 (66.25 KB)
Trainable params: 16,961 (66.25 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/30 510/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0240 - mae: 0.0774 - mse: 0.0240 Epoch 1: val_loss improved from inf to 0.00156, saving model to models/saved/Direct_Refiner_Model_simple_lstm_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 5s 7ms/step - loss: 0.0237 - mae: 0.0768 - mse: 0.0237 - val_loss: 0.0016 - val_mae: 0.0313 - val_mse: 0.0016 - learning_rate: 0.0010 Epoch 2/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - loss: 0.0012 - mae: 0.0272 - mse: 0.0012 Epoch 2: val_loss improved from 0.00156 to 0.00144, saving model to models/saved/Direct_Refiner_Model_simple_lstm_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 8ms/step - loss: 0.0012 - mae: 0.0272 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0301 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 3/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0269 - mse: 0.0012 Epoch 3: val_loss improved from 0.00144 to 0.00137, saving model to models/saved/Direct_Refiner_Model_simple_lstm_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 5ms/step - loss: 0.0012 - mae: 0.0269 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 4/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0276 - mse: 0.0012 Epoch 4: val_loss improved from 0.00137 to 0.00134, saving model to models/saved/Direct_Refiner_Model_simple_lstm_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0276 - mse: 0.0012 - val_loss: 0.0013 - val_mae: 0.0292 - val_mse: 0.0013 - learning_rate: 0.0010 Epoch 5/30 511/517 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 Epoch 5: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 8ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 - val_loss: 0.0016 - val_mae: 0.0322 - val_mse: 0.0016 - learning_rate: 0.0010 Epoch 6/30 511/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 Epoch 6: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 - val_loss: 0.0015 - val_mae: 0.0305 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 7/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0276 - mse: 0.0012 Epoch 7: val_loss did not improve from 0.00134 Epoch 7: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0276 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 8/30 509/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0012 - mae: 0.0269 - mse: 0.0012 Epoch 8: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 7ms/step - loss: 0.0012 - mae: 0.0269 - mse: 0.0012 - val_loss: 0.0013 - val_mae: 0.0292 - val_mse: 0.0013 - learning_rate: 5.0000e-04 Epoch 9/30 512/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0267 - mse: 0.0012 Epoch 9: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0267 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0293 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 10/30 508/517 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - loss: 0.0012 - mae: 0.0270 - mse: 0.0012 Epoch 10: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 5ms/step - loss: 0.0012 - mae: 0.0270 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 11/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 Epoch 11: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0292 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 12/30 507/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 Epoch 12: val_loss did not improve from 0.00134 Epoch 12: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 13/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 Epoch 13: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0268 - mse: 0.0012 - val_loss: 0.0015 - val_mae: 0.0302 - val_mse: 0.0015 - learning_rate: 2.5000e-04 Epoch 14/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0012 - mae: 0.0267 - mse: 0.0012 Epoch 14: val_loss did not improve from 0.00134 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0012 - mae: 0.0267 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 14: early stopping Restoring model weights from the end of the best epoch: 4.
169/169 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step Metric Value 0 MSE 0.001218 1 MAE 0.027667 2 RMSE 0.034902 3 R2 0.277518 4 MAPE 5.310035 5 SMAPE 5.332502 6 SAE 149.040108
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
Registered model 'Direct_Refiner_Model_simple_lstm_simple' already exists. Creating a new version of this model... Created version '4' of model 'Direct_Refiner_Model_simple_lstm_simple'.
Hybrid: Direct Simple + Refine CNN Simple
In [22]:
dir_model = mlflow.keras.load_model("models:/Direct_LSTM_Model_simple/7")
run_direct_refiner_experiment(build_refinement_cnn_model_simple,
dir_model,
'simple_cnn_simple',
'ref_simple_cnn_simple',
X_train_dir=X_train_dir,
X_test_dir=X_test_dir,
X_val_dir=X_val_dir,
y_test_dir=y_test_dir,
y_train_dir=y_train_dir,
y_val_dir=y_val_dir,
output_steps=20,
units=32)
517/517 ━━━━━━━━━━━━━━━━━━━━ 9s 16ms/step 173/173 ━━━━━━━━━━━━━━━━━━━━ 3s 17ms/step 169/169 ━━━━━━━━━━━━━━━━━━━━ 3s 16ms/step (20, 1)
Model: "Base_CNN_Refiner"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ refinement_input (InputLayer) │ (None, 20, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ conv1d_1 (Conv1D) │ (None, 18, 16) │ 64 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ global_max_pooling1d_1 │ (None, 16) │ 0 │ │ (GlobalMaxPooling1D) │ │ │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_8 (Dense) │ (None, 32) │ 544 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ refined_output (Dense) │ (None, 1) │ 33 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 641 (2.50 KB)
Trainable params: 641 (2.50 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/30 493/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0594 - mae: 0.1573 Epoch 1: val_loss improved from inf to 0.00287, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 2s 2ms/step - loss: 0.0574 - mae: 0.1529 - val_loss: 0.0029 - val_mae: 0.0440 - learning_rate: 0.0010 Epoch 2/30 482/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0015 - mae: 0.0305 Epoch 2: val_loss improved from 0.00287 to 0.00253, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0015 - mae: 0.0304 - val_loss: 0.0025 - val_mae: 0.0409 - learning_rate: 0.0010 Epoch 3/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0013 - mae: 0.0289 Epoch 3: val_loss improved from 0.00253 to 0.00183, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0013 - mae: 0.0289 - val_loss: 0.0018 - val_mae: 0.0340 - learning_rate: 0.0010 Epoch 4/30 511/517 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - loss: 0.0012 - mae: 0.0277 Epoch 4: val_loss improved from 0.00183 to 0.00150, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0277 - val_loss: 0.0015 - val_mae: 0.0308 - learning_rate: 0.0010 Epoch 5/30 491/517 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - loss: 0.0012 - mae: 0.0276 Epoch 5: val_loss improved from 0.00150 to 0.00140, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0276 - val_loss: 0.0014 - val_mae: 0.0299 - learning_rate: 0.0010 Epoch 6/30 502/517 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - loss: 0.0012 - mae: 0.0277 Epoch 6: val_loss improved from 0.00140 to 0.00140, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0277 - val_loss: 0.0014 - val_mae: 0.0299 - learning_rate: 0.0010 Epoch 7/30 493/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0276 Epoch 7: val_loss improved from 0.00140 to 0.00139, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0276 - val_loss: 0.0014 - val_mae: 0.0298 - learning_rate: 0.0010 Epoch 8/30 509/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0275 Epoch 8: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0275 - val_loss: 0.0015 - val_mae: 0.0305 - learning_rate: 0.0010 Epoch 9/30 497/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0274 Epoch 9: val_loss improved from 0.00139 to 0.00139, saving model to models/saved/Direct_Refiner_Model_simple_cnn_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0274 - val_loss: 0.0014 - val_mae: 0.0298 - learning_rate: 0.0010 Epoch 10/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0276 Epoch 10: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0276 - val_loss: 0.0015 - val_mae: 0.0305 - learning_rate: 0.0010 Epoch 11/30 486/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0277 Epoch 11: val_loss did not improve from 0.00139 Epoch 11: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0277 - val_loss: 0.0015 - val_mae: 0.0311 - learning_rate: 0.0010 Epoch 12/30 483/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0272 Epoch 12: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0272 - val_loss: 0.0016 - val_mae: 0.0314 - learning_rate: 5.0000e-04 Epoch 13/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - loss: 0.0012 - mae: 0.0276 Epoch 13: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0276 - val_loss: 0.0014 - val_mae: 0.0299 - learning_rate: 5.0000e-04 Epoch 14/30 492/517 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - loss: 0.0012 - mae: 0.0273 Epoch 14: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0273 - val_loss: 0.0014 - val_mae: 0.0298 - learning_rate: 5.0000e-04 Epoch 15/30 493/517 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - loss: 0.0012 - mae: 0.0274 Epoch 15: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0274 - val_loss: 0.0015 - val_mae: 0.0310 - learning_rate: 5.0000e-04 Epoch 16/30 489/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0273 Epoch 16: val_loss did not improve from 0.00139 Epoch 16: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0273 - val_loss: 0.0016 - val_mae: 0.0317 - learning_rate: 5.0000e-04 Epoch 17/30 502/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0274 Epoch 17: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0274 - val_loss: 0.0015 - val_mae: 0.0308 - learning_rate: 2.5000e-04 Epoch 18/30 508/517 ━━━━━━━━━━━━━━━━━━━━ 0s 1ms/step - loss: 0.0012 - mae: 0.0272 Epoch 18: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0272 - val_loss: 0.0015 - val_mae: 0.0304 - learning_rate: 2.5000e-04 Epoch 19/30 501/517 ━━━━━━━━━━━━━━━━━━━━ 0s 2ms/step - loss: 0.0012 - mae: 0.0273 Epoch 19: val_loss did not improve from 0.00139 517/517 ━━━━━━━━━━━━━━━━━━━━ 1s 2ms/step - loss: 0.0012 - mae: 0.0273 - val_loss: 0.0016 - val_mae: 0.0315 - learning_rate: 2.5000e-04 Epoch 19: early stopping Restoring model weights from the end of the best epoch: 9.
169/169 ━━━━━━━━━━━━━━━━━━━━ 0s 981us/step Metric Value 0 MSE 0.001267 1 MAE 0.028260 2 RMSE 0.035598 3 R2 0.248402 4 MAPE 5.413029 5 SMAPE 5.444691 6 SAE 152.234929
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
Registered model 'Direct_Refiner_Model_simple_cnn_simple' already exists. Creating a new version of this model... Created version '5' of model 'Direct_Refiner_Model_simple_cnn_simple'.
Hybrid: Direct Simple + Refine LSTM Average
In [23]:
import importlib
from autoregression.models import RefineLSTM
importlib.reload(RefineLSTM)
from autoregression.models.RefineLSTM import build_average_refinement_lstm
dir_model = mlflow.keras.load_model("models:/Direct_LSTM_Model_simple/7")
run_direct_refiner_experiment(build_average_refinement_lstm,
dir_model,
'simple_lstm_avg',
'ref_simple_lstm_avg',
X_train_dir=X_train_dir,
X_test_dir=X_test_dir,
X_val_dir=X_val_dir,
y_test_dir=y_test_dir,
y_train_dir=y_train_dir,
y_val_dir=y_val_dir,
output_steps=20,
units=64)
517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step 173/173 ━━━━━━━━━━━━━━━━━━━━ 3s 16ms/step 169/169 ━━━━━━━━━━━━━━━━━━━━ 3s 15ms/step (20, 1)
Model: "Refiner_LSTM_Average"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ refinement_input (InputLayer) │ (None, 20, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_11 (LSTM) │ (None, 20, 64) │ 16,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_12 (Dropout) │ (None, 20, 64) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_12 (LSTM) │ (None, 20, 32) │ 12,416 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_13 (Dropout) │ (None, 20, 32) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_13 (LSTM) │ (None, 16) │ 3,136 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_14 (Dropout) │ (None, 16) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_9 (Dense) │ (None, 1) │ 17 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 32,465 (126.82 KB)
Trainable params: 32,465 (126.82 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0288 - mae: 0.1125 - mse: 0.0288 Epoch 1: val_loss improved from inf to 0.00150, saving model to models/saved/Direct_Refiner_Model_simple_lstm_avg.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 13s 17ms/step - loss: 0.0287 - mae: 0.1124 - mse: 0.0287 - val_loss: 0.0015 - val_mae: 0.0310 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 2/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0055 - mae: 0.0584 - mse: 0.0055 Epoch 2: val_loss did not improve from 0.00150 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0055 - mae: 0.0584 - mse: 0.0055 - val_loss: 0.0016 - val_mae: 0.0321 - val_mse: 0.0016 - learning_rate: 0.0010 Epoch 3/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0037 - mae: 0.0484 - mse: 0.0037 Epoch 3: val_loss improved from 0.00150 to 0.00135, saving model to models/saved/Direct_Refiner_Model_simple_lstm_avg.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 16ms/step - loss: 0.0037 - mae: 0.0484 - mse: 0.0037 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 4/30 513/517 ━━━━━━━━━━━━━━━━━━━━ 0s 15ms/step - loss: 0.0028 - mae: 0.0420 - mse: 0.0028 Epoch 4: val_loss improved from 0.00135 to 0.00135, saving model to models/saved/Direct_Refiner_Model_simple_lstm_avg.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 16ms/step - loss: 0.0028 - mae: 0.0420 - mse: 0.0028 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 5/30 513/517 ━━━━━━━━━━━━━━━━━━━━ 0s 15ms/step - loss: 0.0021 - mae: 0.0361 - mse: 0.0021 Epoch 5: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 16ms/step - loss: 0.0021 - mae: 0.0361 - mse: 0.0021 - val_loss: 0.0015 - val_mae: 0.0305 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 6/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0017 - mae: 0.0319 - mse: 0.0017 Epoch 6: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0017 - mae: 0.0319 - mse: 0.0017 - val_loss: 0.0015 - val_mae: 0.0309 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 7/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0014 - mae: 0.0295 - mse: 0.0014 Epoch 7: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 7s 14ms/step - loss: 0.0014 - mae: 0.0295 - mse: 0.0014 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 8/30 513/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0014 - mae: 0.0289 - mse: 0.0014 Epoch 8: val_loss did not improve from 0.00135 Epoch 8: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0014 - mae: 0.0289 - mse: 0.0014 - val_loss: 0.0014 - val_mae: 0.0297 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 9/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 Epoch 9: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0298 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 10/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 15ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 Epoch 10: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 16ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 - val_loss: 0.0015 - val_mae: 0.0307 - val_mse: 0.0015 - learning_rate: 5.0000e-04 Epoch 11/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 Epoch 11: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 7s 14ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0298 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 12/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 Epoch 12: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 7s 14ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 13/30 513/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0012 - mae: 0.0276 - mse: 0.0012 Epoch 13: val_loss did not improve from 0.00135 Epoch 13: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0012 - mae: 0.0276 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0301 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 14/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0012 - mae: 0.0277 - mse: 0.0012 Epoch 14: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0012 - mae: 0.0277 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0297 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 14: early stopping Restoring model weights from the end of the best epoch: 4.
169/169 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step Metric Value 0 MSE 0.001248 1 MAE 0.028046 2 RMSE 0.035321 3 R2 0.260060 4 MAPE 5.369473 5 SMAPE 5.409736 6 SAE 151.083580
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step
Registered model 'Direct_Refiner_Model_simple_lstm_avg' already exists. Creating a new version of this model... Created version '6' of model 'Direct_Refiner_Model_simple_lstm_avg'.
Hybrid: Direct Average + Refine LSTM Simple
In [24]:
dir_model_av = mlflow.keras.load_model("models:/Direct_LSTM_Model_average/6")
dir_model_av.summary()
run_direct_refiner_experiment(build_refinement_lstm_model_simple,
dir_model_av,
'avg_lstm_simple',
'ref_avg_lstm_simple',
X_train_dir=X_train_dir,
X_test_dir=X_test_dir,
X_val_dir=X_val_dir,
y_test_dir=y_test_dir,
y_train_dir=y_train_dir,
y_val_dir=y_val_dir,
output_steps=20,
units=64)
Model: "Avarege_Direct_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ input_layer (InputLayer) │ (None, 100, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional (Bidirectional) │ (None, 100, 512) │ 528,384 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout (Dropout) │ (None, 100, 512) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ bidirectional_1 (Bidirectional) │ (None, 256) │ 656,384 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_1 (Dropout) │ (None, 256) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense (Dense) │ (None, 128) │ 32,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_2 (Dropout) │ (None, 128) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_1 (Dense) │ (None, 20) │ 2,580 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 3,660,734 (13.96 MB)
Trainable params: 1,220,244 (4.65 MB)
Non-trainable params: 0 (0.00 B)
Optimizer params: 2,440,490 (9.31 MB)
517/517 ━━━━━━━━━━━━━━━━━━━━ 39s 73ms/step 173/173 ━━━━━━━━━━━━━━━━━━━━ 13s 72ms/step 169/169 ━━━━━━━━━━━━━━━━━━━━ 13s 74ms/step (20, 1)
Model: "Refinement_LSTM_Model"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ refinement_input (InputLayer) │ (None, 20, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ refinement_lstm (LSTM) │ (None, 64) │ 16,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ refined_20th_output (Dense) │ (None, 1) │ 65 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 16,961 (66.25 KB)
Trainable params: 16,961 (66.25 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/30 510/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0131 - mae: 0.0626 - mse: 0.0131 Epoch 1: val_loss improved from inf to 0.00137, saving model to models/saved/Direct_Refiner_Model_avg_lstm_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 6s 7ms/step - loss: 0.0130 - mae: 0.0622 - mse: 0.0130 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 2/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0013 - mae: 0.0281 - mse: 0.0013 Epoch 2: val_loss did not improve from 0.00137 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0013 - mae: 0.0281 - mse: 0.0013 - val_loss: 0.0015 - val_mae: 0.0310 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 3/30 508/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 Epoch 3: val_loss did not improve from 0.00137 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0300 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 4/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 Epoch 4: val_loss did not improve from 0.00137 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0296 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 5/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - loss: 0.0013 - mae: 0.0286 - mse: 0.0013 Epoch 5: val_loss did not improve from 0.00137 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 8ms/step - loss: 0.0013 - mae: 0.0286 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0296 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 6/30 512/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 Epoch 6: val_loss did not improve from 0.00137 Epoch 6: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 7ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0299 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 7/30 511/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 Epoch 7: val_loss improved from 0.00137 to 0.00135, saving model to models/saved/Direct_Refiner_Model_avg_lstm_simple.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0292 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 8/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 Epoch 8: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 7ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 9/30 511/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 Epoch 9: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0293 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 10/30 509/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 Epoch 10: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0293 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 11/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0013 - mae: 0.0276 - mse: 0.0013 Epoch 11: val_loss did not improve from 0.00135 Epoch 11: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0013 - mae: 0.0276 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0292 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 12/30 510/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0274 - mse: 0.0012 Epoch 12: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0274 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0297 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 13/30 511/517 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - loss: 0.0012 - mae: 0.0274 - mse: 0.0012 Epoch 13: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 8ms/step - loss: 0.0012 - mae: 0.0274 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0293 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 14/30 512/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 Epoch 14: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 - val_loss: 0.0015 - val_mae: 0.0305 - val_mse: 0.0015 - learning_rate: 2.5000e-04 Epoch 15/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 Epoch 15: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 3s 6ms/step - loss: 0.0012 - mae: 0.0275 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0300 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 16/30 512/517 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - loss: 0.0012 - mae: 0.0272 - mse: 0.0012 Epoch 16: val_loss did not improve from 0.00135 Epoch 16: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814. 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0012 - mae: 0.0273 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0293 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 17/30 509/517 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - loss: 0.0012 - mae: 0.0273 - mse: 0.0012 Epoch 17: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - loss: 0.0012 - mae: 0.0273 - mse: 0.0012 - val_loss: 0.0014 - val_mae: 0.0299 - val_mse: 0.0014 - learning_rate: 1.2500e-04 Epoch 17: early stopping Restoring model weights from the end of the best epoch: 7.
169/169 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step Metric Value 0 MSE 0.001238 1 MAE 0.027908 2 RMSE 0.035182 3 R2 0.265881 4 MAPE 5.355531 5 SMAPE 5.379587 6 SAE 150.342313
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 36ms/step
Registered model 'Direct_Refiner_Model_avg_lstm_simple' already exists. Creating a new version of this model... Created version '4' of model 'Direct_Refiner_Model_avg_lstm_simple'.
Hybrid: Direct Average + Refine LSTM Average
In [25]:
dir_model = mlflow.keras.load_model("models:/Direct_LSTM_Model_average/6")
run_direct_refiner_experiment(build_average_refinement_lstm,
dir_model,
'avg_lstm_avg',
'ref_avg_lstm_avg',
X_train_dir=X_train_dir,
X_test_dir=X_test_dir,
X_val_dir=X_val_dir,
y_test_dir=y_test_dir,
y_train_dir=y_train_dir,
y_val_dir=y_val_dir,
output_steps=20,
units=64)
517/517 ━━━━━━━━━━━━━━━━━━━━ 39s 75ms/step 173/173 ━━━━━━━━━━━━━━━━━━━━ 12s 72ms/step 169/169 ━━━━━━━━━━━━━━━━━━━━ 12s 71ms/step (20, 1)
Model: "Refiner_LSTM_Average"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩ │ refinement_input (InputLayer) │ (None, 20, 1) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_14 (LSTM) │ (None, 20, 64) │ 16,896 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_15 (Dropout) │ (None, 20, 64) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_15 (LSTM) │ (None, 20, 32) │ 12,416 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_16 (Dropout) │ (None, 20, 32) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ lstm_16 (LSTM) │ (None, 16) │ 3,136 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dropout_17 (Dropout) │ (None, 16) │ 0 │ ├─────────────────────────────────┼────────────────────────┼───────────────┤ │ dense_10 (Dense) │ (None, 1) │ 17 │ └─────────────────────────────────┴────────────────────────┴───────────────┘
Total params: 32,465 (126.82 KB)
Trainable params: 32,465 (126.82 KB)
Non-trainable params: 0 (0.00 B)
Epoch 1/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0198 - mae: 0.0955 - mse: 0.0198 Epoch 1: val_loss improved from inf to 0.00349, saving model to models/saved/Direct_Refiner_Model_avg_lstm_avg.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 11s 15ms/step - loss: 0.0197 - mae: 0.0954 - mse: 0.0197 - val_loss: 0.0035 - val_mae: 0.0497 - val_mse: 0.0035 - learning_rate: 0.0010 Epoch 2/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0051 - mae: 0.0570 - mse: 0.0051 Epoch 2: val_loss improved from 0.00349 to 0.00159, saving model to models/saved/Direct_Refiner_Model_avg_lstm_avg.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0051 - mae: 0.0569 - mse: 0.0051 - val_loss: 0.0016 - val_mae: 0.0316 - val_mse: 0.0016 - learning_rate: 0.0010 Epoch 3/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0036 - mae: 0.0473 - mse: 0.0036 Epoch 3: val_loss improved from 0.00159 to 0.00136, saving model to models/saved/Direct_Refiner_Model_avg_lstm_avg.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0036 - mae: 0.0473 - mse: 0.0036 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 4/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0026 - mae: 0.0398 - mse: 0.0026 Epoch 4: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 16ms/step - loss: 0.0026 - mae: 0.0398 - mse: 0.0026 - val_loss: 0.0015 - val_mae: 0.0311 - val_mse: 0.0015 - learning_rate: 0.0010 Epoch 5/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0019 - mae: 0.0345 - mse: 0.0019 Epoch 5: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 10s 16ms/step - loss: 0.0019 - mae: 0.0345 - mse: 0.0019 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 6/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0016 - mae: 0.0313 - mse: 0.0016 Epoch 6: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0016 - mae: 0.0313 - mse: 0.0016 - val_loss: 0.0016 - val_mae: 0.0321 - val_mse: 0.0016 - learning_rate: 0.0010 Epoch 7/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0015 - mae: 0.0305 - mse: 0.0015 Epoch 7: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0015 - mae: 0.0305 - mse: 0.0015 - val_loss: 0.0014 - val_mae: 0.0296 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 8/30 513/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0014 - mae: 0.0293 - mse: 0.0014 Epoch 8: val_loss did not improve from 0.00136 Epoch 8: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257. 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0014 - mae: 0.0293 - mse: 0.0014 - val_loss: 0.0014 - val_mae: 0.0294 - val_mse: 0.0014 - learning_rate: 0.0010 Epoch 9/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 15ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 Epoch 9: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 16ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0296 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 10/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0288 - mse: 0.0013 Epoch 10: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0288 - mse: 0.0013 - val_loss: 0.0017 - val_mae: 0.0331 - val_mse: 0.0017 - learning_rate: 5.0000e-04 Epoch 11/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 Epoch 11: val_loss did not improve from 0.00136 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 - val_loss: 0.0016 - val_mae: 0.0321 - val_mse: 0.0016 - learning_rate: 5.0000e-04 Epoch 12/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0283 - mse: 0.0013 Epoch 12: val_loss improved from 0.00136 to 0.00135, saving model to models/saved/Direct_Refiner_Model_avg_lstm_avg.keras 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0283 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0292 - val_mse: 0.0014 - learning_rate: 5.0000e-04 Epoch 13/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 Epoch 13: val_loss did not improve from 0.00135 Epoch 13: ReduceLROnPlateau reducing learning rate to 0.0002500000118743628. 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 16ms/step - loss: 0.0013 - mae: 0.0285 - mse: 0.0013 - val_loss: 0.0015 - val_mae: 0.0306 - val_mse: 0.0015 - learning_rate: 5.0000e-04 Epoch 14/30 514/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 Epoch 14: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 - val_loss: 0.0015 - val_mae: 0.0303 - val_mse: 0.0015 - learning_rate: 2.5000e-04 Epoch 15/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0281 - mse: 0.0013 Epoch 15: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0281 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0293 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 16/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0013 - mae: 0.0284 - mse: 0.0013 Epoch 16: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0284 - mse: 0.0013 - val_loss: 0.0016 - val_mae: 0.0321 - val_mse: 0.0016 - learning_rate: 2.5000e-04 Epoch 17/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0284 - mse: 0.0013 Epoch 17: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0284 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0301 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 18/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 Epoch 18: val_loss did not improve from 0.00135 Epoch 18: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814. 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0280 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0296 - val_mse: 0.0014 - learning_rate: 2.5000e-04 Epoch 19/30 517/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0281 - mse: 0.0013 Epoch 19: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0281 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0297 - val_mse: 0.0014 - learning_rate: 1.2500e-04 Epoch 20/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0013 - mae: 0.0282 - mse: 0.0013 Epoch 20: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0282 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 1.2500e-04 Epoch 21/30 515/517 ━━━━━━━━━━━━━━━━━━━━ 0s 13ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 Epoch 21: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0279 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0295 - val_mse: 0.0014 - learning_rate: 1.2500e-04 Epoch 22/30 516/517 ━━━━━━━━━━━━━━━━━━━━ 0s 14ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 Epoch 22: val_loss did not improve from 0.00135 517/517 ━━━━━━━━━━━━━━━━━━━━ 8s 15ms/step - loss: 0.0013 - mae: 0.0278 - mse: 0.0013 - val_loss: 0.0014 - val_mae: 0.0297 - val_mse: 0.0014 - learning_rate: 1.2500e-04 Epoch 22: early stopping Restoring model weights from the end of the best epoch: 12.
169/169 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step Metric Value 0 MSE 0.001241 1 MAE 0.027964 2 RMSE 0.035229 3 R2 0.263927 4 MAPE 5.353449 5 SMAPE 5.392957 6 SAE 150.639978
1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step
Registered model 'Direct_Refiner_Model_avg_lstm_avg' already exists. Creating a new version of this model... Created version '5' of model 'Direct_Refiner_Model_avg_lstm_avg'.